ACM Transactions on

Design Automation of Electronic Systems (TODAES)

Latest Articles

Security Analysis of Arbiter PUF and Its Lightweight Compositions Under Predictability Test

Unpredictability is an important security property of Physically Unclonable Function (PUF) in the context of statistical attacks, where the... (more)


With the emergence of many-core multiprocessor system-on-chips (MPSoCs), on-chip networks are facing serious challenges in providing fast communication among various tasks and cores. One promising on-chip network design approach shown in recent studies is to add express channels to traditional mesh network as shortcuts to bypass intermediate... (more)

Scalable SMT-Based Equivalence Checking of Nested Loop Pipelining in Behavioral Synthesis

In this article, we present a novel methodology based on SMT-solvers to verify equality of a high-level described specification and a pipelined RTL... (more)

Optimized Implementation of Multirate Mixed-Criticality Synchronous Reactive Models

Model-based design using Synchronous Reactive (SR) models enables early design and verification of application functionality in a platform-independent... (more)

Reducing the Complexity of Dataflow Graphs Using Slack-Based Merging

There exist many dataflow applications with timing constraints that require real-time guarantees on safe execution without violating their deadlines.... (more)

On the Restore Time Variations of Future DRAM Memory

As the de facto main memory standard, DRAM (Dynamic Random Access Memory) has achieved dramatic density improvement in the past four decades, along... (more)

A Hybrid DRAM/PCM Buffer Cache Architecture for Smartphones with QoS Consideration

Flash memory is widely used in mobile phones to store contact information, application files, and other types of data. In an operating system, the... (more)

An Elastic Mixed-Criticality Task Model and Early-Release EDF Scheduling Algorithms

Many algorithms have recently been studied for scheduling mixed-criticality (MC) tasks. However, most existing MC scheduling algorithms guarantee the... (more)

Computation of Seeds for LFSR-Based n-Detection Test Generation

This article describes a new procedure that generates seeds for LFSR-based test generation when the goal is to produce an n-detection test set. The... (more)

Scale & Cap

As the number of cores per server node increases, designing multi-threaded applications has become essential to efficiently utilize the available hardware parallelism. Many application domains have started to adopt multi-threaded programming; thus, efficient management of multi-threaded applications has become a significant research problem.... (more)

Secure and Flexible Trace-Based Debugging of Systems-on-Chip

This work tackles the conflict between enforcing security of a system-on-chip (SoC) and providing observability during trace-based debugging. On one... (more)

A MATLAB Vectorizing Compiler Targeting Application-Specific Instruction Set Processors

This article discusses a MATLAB-to-C vectorizing compiler that exploits custom instructions, for... (more)


Best Paper Award: Congratulations to Chung-Wei Lin, Bowen Zheng, Qi Zhu, and Alberto Sangiovanni-Vincentelli on receiving the 2016 ACM TODAES Best Paper Award for their article titled Security-Aware Design Methodology and Optimization for Automotive Systems, ACM Transactions on Design Automation of Electronic Systems (TODAES), Volume 21, Issue 1, Article 18, November 2015.

ACM TODAES new page limit policy: Manuscripts must be formatted in the ACM Transactions format; a 25-page limit applies to the final paper. Rare exceptions are possible if recommended by the reviewers and approved by the Editorial Board.

ORCID is a community-based effort to create a global registry of unique researcher identifiers for the purpose of ensuring proper attribution of works to their creators. When you submit a manuscript for review, you will be presented with the opportunity to register for your ORCID.

Forthcoming Articles
HoPE: Hot-cacheline Prediction for Dynamic Early Decompression in Compressed LLCs

Data compression plays a pivotal role in improving system performance and reducing energy consumption, because it increases the logical effective capacity of a compressed memory system without physically increasing the memory size. However, data compression techniques incur some cost, such as non-negligible compression and decompression overhead. This overhead becomes more severe if compression is used in the cache. In this paper, we aim to lower the read-hit decompression penalty, which significantly increases the cache memory access latency. We demonstrate that the speculative decompression of frequently used cachelines can significantly reduce the read-hit decompression penalty. We hereby propose a Hot-cacheline Prediction and Early decompression (HoPE) mechanism to determine when a compressed cacheline should be decompressed, in order to minimize the total execution time of the system. Additionally, we show that cachelines of similar compressibility often have a high correlation in their hit rates, as data with similar structures is often used in similar ways. Building on this insight, we also propose a compressed cacheline Hit-history-Based Insertion (HBI) policy to take advantage of this correlation, by predicting how often a cacheline will be hit, based on its compressibility. To evaluate the effectiveness of the proposed HoPE mechanism, we run extensive simulations on memory traces obtained from multi-threaded benchmarks running on a full-system simulation framework. We observe significant performance improvements over compressed cache schemes employing the conventional Least-Recently Used (LRU) replacement policy, the Dynamic Re-Reference Interval Prediction (DRRIP) scheme, and the ECM compressed cache management mechanism. Specifically, HoPE exhibits system performance improvements of approximately 11%, on average, over LRU, 8% over DRRIP, and 7% over ECM, by reducing the read-hit decompression penalty by around 65%, over a wide range of applications.

Approximate Energy-Efficient Encoding for Serial Interfaces

Serial buses are ubiquitous interconnections in embedded computing systems that are used to interface processing elements with peripherals, such as sensors, actuators and I/O controllers. In spite of their limited wiring, as off-chip connections they can account for a significant amount of the total power consumption of a system-on-chip device. Encoding the information sent on these buses is the most intuitive and affordable way to reduce their power contribution; moreover, the encoding can me made even more effective by exploiting the fact that many embedded applications can tolerate intermediate approximations without a significant impact on the final quality of results, thus trading off accuracy for power consumption. We propose a simple yet very effective approximate encoding for reducing dynamic energy in serial buses. Our approach uses differential encoding as a baseline scheme, and extends it with bounded approximations to overcome the intrinsic limitations of differential encoding for data with low temporal correlation. We show that the proposed scheme, besides yielding extremely compact codecs, is superior to all state-of-the-art approximate serial encodings over a wide set of traces representing data received or sent from/to sensor or actuators.

SSAGA: SMs Synthesized for Asymmetric GPGPU Applications

Emergence of GPGPU applications, bolstered by flexible GPU programming platforms, has created a tremendous challenge in maintaining a high energy efficiency in modern GPUs. In this paper, we demonstrate that, customizing a Streaming Multiprocessor (SM) of a GPU, at a lower frequency, is significantly more energy efficient, compared to employing DVFS on an SM, designed for a high frequency operation. Using a system level CAD technique, we propose SSAGAStreaming Multiprocessors Sculpted for Asymmetric GPGPU Applications, an energy efficient GPU design paradigm. SSAGA creates architecturally identical SM cores, customized for different voltage-frequency domains. Our rigorous cross-layer methodology demonstrates an average of 20% improvement in energy efficiency, over a spatially multitasking GPU, across a range of GPGPU applications.

Layer Assignment of Escape buses with Consecutive Constraints in PCB Designs

It is known that it is important for cost and reliability consideration to minimize the number of the used layers and assign the escape buses onto the available layers in a PCB design. In this paper, given a set of n escape buses between two adjacent components and a set of m consecutive constraints on the escape buses, the problem of assigning the given escape buses between two adjacent components onto the available layers is formulated in bus-oriented escape routing. Furthermore, an efficient approach is proposed to minimize the number of the used layers for the given escape buses with the consecutive constraints and assign the escape buses onto the available layers. Compared with Yans approach [J. T. Yan et al. 2012] for the layer assignment of the linear escape buses with no consecutive constraint and Mas approach [Q. Ma, F. Y. Young et al. 2011] for the layer assignment of the circular escape buses with consecutive constraints, the experimental results show that our proposed approach obtains betterl results on the number of the used layers and reduces 43.6% and 90.5% of CPU time for the tested examples on the average, respectively.

Generation of Transparent-Scan Sequences for Diagnosis of Scan Chain Faults

Diagnosis of scan chain faults is important for yield learning and improvement. Procedures that generate tests for diagnosis of scan chain faults produce scan-based tests with one or more functional capture cycles between a scan-in and a scan-out operation. The approach to test generation referred to as transparent-scan has several advantages in this context. (1) It allows functional capture cycles and scan shift cycles to be interleaved arbitrarily. This increases the flexibility to assign to the scan cells values that are needed for diagnosis. (2) Test generation under transparent-scan considers a circuit model where the scan logic is included explicitly. Consequently, the test generation procedure takes into consideration the full effect of a scan chain fault. It thus produces accurate tests. (3) For the same reason it can also target faults inside the scan logic. (4) Transparent-scan results in compact test sequences. Compaction is important because of the large volumes of fail data that scan chain faults create. The cost of transparent-scan is that it requires simulation procedures for sequential circuits, and that arbitrary sequences would be applicable to the scan select input. Motivated by the advantages of transparent-scan, and the importance of diagnosing scan chain faults, this paper describes a procedure for generating transparent-scan sequences for diagnosis of scan chain faults. The procedure is also applied to produce transparent-scan sequences for diagnosis of faults inside the scan logic.

Topological Approach to Automatic Symbolic Macromodel Generation for Analog ICs

In the field of analog integrated circuit design, small-signal macromodels play indispensable roles. However, the subject of automatically generating symbolic low-order macromodels in human readable circuit form has not been well studied. Traditionally, work has been published on reducing full-scale symbolic transfer functions to simpler forms, but without the guarantee of interpretability. In this work a topological reduction method is introduced which is able to automatically generate interpretable macromodel circuits in symbolic form; that is, the circuit elements in the compact model maintain analytical relations of the parameters of the original full circuit. This type of symbolic macromodel has several benefits that other traditional modeling methods do not offer: firstly, reusability, namely, designer need not repeatedly generate macromodels for the same analog integrated circuit when it is either resized or rebiased; secondly, interpretability, namely, designer may identify directly circuit parameters in the original integrated circuit that are closely related to the dominant frequency characteristics, such as dc gain, gain/phase margins, and dominant poles/zeros, etc. The effectiveness and computational efficiency of the proposed method have been validated by several operational amplifier (opamp) circuit examples.

Generating Current Constraints to Guarantee RLC Power Grid Safety

A critical task during early chip design is the efficient verification of the chip power distribution network. Vectorless verification, developed over the last decade as an alternative to traditional simulation-based methods, requires the user to specify current constraints (budgets) for the underlying circuitry and checks if the corresponding voltage variations on all grid nodes are within a user-specified margin. This framework is extremely powerful as it allows for efficient and early verification, but specifying/obtaining current constraints remains a burdensome task for users and a hurdle to adoption of this framework by the industry. Recently, the inverse problem has been introduced: generate circuit current constraints that, if satisfied by the underlying logic circuitry, would guarantee grid safety from excessive voltage variations. This approach has many potential applications, including various grid quality metrics, as well as voltage drop aware placement and floorplanning. So far, this framework has been developed assuming an RC model of the power grid. Inductive effects are becoming a significant component of the power supply noise and can no longer be ignored. In this paper, we extend the constraints generation approach to allow for inductance. We give a rigorous problem definition and develop some key theoretical results related to maximality of the current space defined by the constraints. Based on this, we then develop three constraints generation algorithms that target the peak total chip power that is allowed by the grid, the uniformity of current distribution across the die area, and a combination of both metrics.

Leak Stopper: An Actively Revitalized Snoop Filter Architecture with Effective Generation Control

To alleviate high energy dissipation of unnecessary snooping accesses, snoop filter designs have been proposed to reduce snoop lookups. These filters have the problem of decreasing filtering efficiency, and thus usually rely on partial or whole filter reset by detecting block evictions. Unfortunately, the reset conditions occur infrequently or unevenly (named as passive filter deletion). This work proposes the concept of revitalized snoop filter (RSF) design, which can actively renew the destination filter by employing a generation wrapping around scheme for various reference behaviors. We further utilize a sampling mechanism for RSF to timely trigger precise filter revitalizations, so that unnecessary RSF flushing can be minimized. The proposed RSF can be integrated to various inclusive snoop filters and needs only minor change to their designs. We evaluate our proposed design and demonstrate that RSF eliminates 58.6% of snoop energy compared to JETTY on average while inducing only 6.5% of revitalization energy overhead. In addition, RSF eliminates 45.5% of snoop energy compared to stream registers on average and only induces 2.5% of revitalization energy overhead. Overall, these RSFs reduce the total L2 cache energy consumption by 52.1% (58.6%-6.5%) as compared to JETTY and by 43% (45.5%-2.5%) as compared to stream registers. Furthermore, RSF improves the overall performance by 1% to 1.4% on average compared to JETTY and Stream Registers for various benchmark suites.

A Single-Tier Virtual Queuing Memory Controller Architecture for Heterogeneous MPSoCs

Heterogeneous MPSoCs typically integrate diverse cores, including application CPUs, GPUs, and HD coders. These cores commonly share an off-chip memory to save cost and energy, but their memory accesses often interfere with each other, leading to undesirable consequences like a slowdown of application performance or a failure to sustain real-time performance. The memory controller plays a central role in meeting the QoS needs of real-time cores while maximizing the CPU performance. Previous QoS-aware memory controllers are based on a classic two-tier queuing architecture that buffers memory transactions at the first tier, followed by a second tier that buffers translated DRAM commands. In these designs, QoS-aware policies are used to schedule competing transactions at the first stage, but the translated DRAM commands are serviced in FIFO order at the second stage. Unfortunately, once the scheduled transactions have been forwarded to the command stage, newly arriving transactions that may be more critical cannot be serviced ahead of those translated commands that are already queued at the second stage. To address this, we propose a scalable memory controller architecture based on Single-Tier Virtual Queuing (STVQ) that maintains a single-tier of request queues and employs an efficacious scheduler that considers both QoS requirements and DRAM bank states. In comparison with previous QoS-aware memory controllers, the proposed STVQ memory controller reduces CPU slowdown by up to 13.9% while satisfying all frame rate requirements. We propose further optimizations that can significantly increase row-buffer hits by up to 66.2% and reduce memory latency by up to 19.8%.

A List of Fundamental Challenges Towards Making IoT a Reachable Reality: A Model-centric Investigation

The constantly advancing integration capability is paving the way to the construction of extremely large scale continuum of internet where entities, or things, from vastly varied domains are uniquely address- able and interacting seamlessly to form a giant networked system of systems, known as Internet-of-things (IoT). In contrast to such visionary networked system paradigm, prior research efforts on IoT are still very fragmented and confined to disjoint explorations in different application, architectural, security, services, protocol and economical domains, thus preventing the design exploration and optimization from a unified and global perspective. In this context, this survey article first proposes a mathematical modeling frame- work that is rich in expressivity to capture the IoT characteristics from a global perspective. Then a list of fundamental challenges in i) sensing , ii) decentralized computation, iii) energy-efficiency and iv) hardware security is identified and formulated based on the proposed modeling framework. The solutions are discussed to shed lights on future IoT system paradigm development.

Proof-Carrying Hardware via IC3

Proof-carrying hardware is a principle for achieving safety for dynamically reconfigurable hardware systems. The producer of a hardware module spends the huge effort for creating a proof for a safety policy. The proof is then transferred as a certificate together with the configuration bitstream to the consumer of the hardware module, who can quickly verify the given proof. Previous work utilized SAT solvers and resolution traces to set up a proof-carrying hardware technology and corresponding tool flows. In this paper, we present a novel technology for proof-carrying hardware based on inductive invariants. For sequential circuits, our approach is fundamentally stronger than the previous SAT-based one since we avoid the limitations of bounded unrolling. We contrast our technology with existing ones and show that it fits into previously proposed tool flows. We conduct experiments with three categories of benchmark circuits and report consumer and producer runtime and peak memory consumption, as well as the size of the certificates and the distribution of the workload between producer and consumer. Experiments clearly show that our new induction-based technology is superior for sequential circuits, while the previous SAT-based technology is the better choice for combinational circuits.

Low-Power Clock Tree Synthesis for 3D-ICs

We propose efficient algorithms to construct low-power clock tree for through-silicon-via (TSV) based 3D-ICs. We use shutdown gates to save clock tree's dynamic power, which selectively turn off certain clock tree branches to avoid unnecessary clock activities when the modules in these tree branches are inactive. While this clock gating technique has been extensively studied in 2D circuits, its application in 3D-ICs is unclear. In 3D-ICs, a shutdown gate is connected to control signal unit through control TSVs, which may cause placement conflicts with existing clock TSVs in the layout due to TSV's large physical dimension. We develop a two-phase clock tree synthesis design flow for 3D-ICs: (1) 3D abstract clock tree generation based on K-means clustering. (2) Clock tree embedding with simultaneous shutdown gates insertion based on simulated annealing (SA) and a force-directed TSV placer. Experimental results indicate that: (1) The K-means clustering heuristic significantly reduces the clock power by clustering modules with similar switching behavior and close proximity. (2) The SA algorithm effectively inserts the shutdown gates to a 3D clock tree, while considering control TSV's placement. Compared with previous 3D clock tree synthesis technique, our K-means clustering based approach achieves larger reduction in clock tree power consumption while ensuring zero clock skew.

Optimal Scheduling and Allocation for IC Design Management and Cost Reduction

A large semiconductor product company spends hundreds of millions of dollars each year on design infrastructure to meet tapeout schedules for multiple concurrent projects. Resources (servers, EDA tool licenses, engineers, etc.) are limited and must be shared  and the cost per day of schedule slip can be enormous. Co-constraints between resource types (e.g., one license per every two cores (threads)) and dedicated versus shareable resource pools make scheduling and allocation hard. In this paper, we formulate two mixed integer-linear programs for optimal multi-project, multi-resource allocation with task precedence and resource co-constraints. Application to a real-world three-project scheduling problem extracted from a leading-edge design center of anonymized Company X shows substantial compute and license costs savings. Compared to the product company, our solution shows that the makespan of schedule of all projects can be reduced by seven days, which not only saves ~2.7% of annual labor and infrastructure costs, but also enhances market competitiveness. We also demonstrate the capability of scheduling over two dozen chip development projects at the design center level, subject to resource and datacenter capacity limits as well as per-project penalty functions for schedule slips. The design center ended up purchasing 600 additional servers, whereas our solution demonstrates that the schedule can be met without having to purchase any additional servers. Application to a four-project scheduling problem extracted from a leading-edge design center in a non-U.S. location shows availability of up to ~37% headcount reduction during a half-year schedule for just one type of chip design activity.

A Fast Hierarchical Adaptive Analog Routing Algorithm based on Integer Linear Programming

The shrinking design window and high parasitic sensitivity in the advanced technology have imposed special challenges to the analog and RF integrated circuit designers. The state-of-the-art analog routing research tends to favor linear programming to achieve various analog constraints, which, although effective, fails to offer high routing efficiency on its own. In this paper, we propose a new methodology to address such a deficiency based on integer linear programming (ILP) but without compromising the capability of handling any special constraints for the analog routing problems. Our proposed method supports hierarchical routing, which can divide the entire routing area into multiple small heterogeneous regions where the ILP can efficiently derive routing solutions. Distinct from the conventional methods, our algorithm utilizes adaptive resolutions for various routing regions. For a more congested region, a routing grid with higher resolution is employed, whereas a lower-resolution grid is adopted to a less crowded routing region. For a large empty space, routing efficiency can be even boosted by creating more routing hierarchy levels. This scheme is especially beneficial to the analog and RF layouts, which are far sparser than the digital counterpart. The experimental results show that our proposed adaptive ILP-based router is much faster than the conventional ones since it spends much less time for the areas that need no accurate routing anyway. The high efficiency is demonstrated for large circuits and especially sparse layouts along with promising routing quality in terms of analog constraints.

PeaPaw: Performance and Energy Aware Partitioning of Workload on Heterogeneous Platforms

Performance and energy are two major concerns for application development on heterogeneous platforms. It is challenging for application developers to fully exploit the performance/energy potential of heterogeneous platforms. One reason is the lack of reliable prediction of the system's performance/energy before application implementation. Another reason is that a heterogeneous platform presents a large design space for workload partitioning between different processors. To reduce such development cost, this paper proposes a framework, PeaPaw, to assist application developers to identify a workload partition (WP) that has high potential leading to high performance or energy efficiency before actual implementation. The PeaPaw framework includes both analytical performance/energy models and two sets of workload partitioning guidelines. Based on the design goal, application developers can obtain a workload partitioning guideline from PeaPaw for a given platform and then follow it to design one or multiple WPs for a given workload. Then PeaPaw can be used to estimate the performance or energy of the designed WPs, and the WP with the best estimated performance or energy will be selected for further implementation. To demonstrate the effectiveness of PeaPaw, we have conducted three case studies. Results from these case studies show that PeaPaw can faithfully estimate the performance/energy relationships of WPs and provide effective workload partitioning guidelines.

Application-Specific Residential Microgrid Design Methodology

In power system industry, the traditional, non-interactive, and manually-controlled power grid has been transformed to cyber-dominated smart grid. This cyber-physical integration has provided the smart grid with communication, monitoring, computation, and controlling capabilities to improve its reliability, energy efficiency, and flexibility. A microgrid as a localized and semi-autonomous group of smart energy systems, utilizes the above-mentioned capabilities to drive modern technologies such as electric vehicle charging, home energy management, smart appliances, etc. Designing, upgrading, testing, and verifying these microgrids can get too complicated to handle manually. The complexity is due to the wide range of solutions and components that are intended to address the microgrid problems. This paper presents a novel Model-Based Design (MBD) methodology to model, co-simulate, design, and optimize microgrid and its multi-level controllers. It helps us to design, optimize, and validate a microgrid for a specific application. The application rules, requirements, and design-time constraints are met in the designed/optimized microgrid while the implementation cost is minimized. Based on our novel methodology, a design automation, co-simulation, and analysis tool, called GridMAT, is implemented. Our experiments have illustrated that implementing a hierarchical controller reduces the average power consumption by 8% and shifts the peak load for cost saving. Moreover, using our MBD methodology with smart controllers, the total implementation cost decreases by 14%, when upgrading a microgrid, compared to the conventional methodology and 5%, compared to the case where smart controllers are not considered.

Using CoreSight PTM to integrate CRA monitoring IPs in an ARM-based SoC

ARM CoreSight PTM has been widely deployed in recent ARM processors for real-time debugging and tracing of software. Using PTM, the external debugger can extract execution behaviors of applications running on an ARM processor. Recently, some researchers begin to use this feature for other purposes such as fault tolerant computation and security monitoring. This motivated us to develop an external security monitor that can detect control hijacking attacks, of which goal is to maliciously manipulate the control flow of victim applications at attackers disposal. Especially, this paper focuses on detecting a special type of attacks, called code reuse attacks (CRA), which uses a recently-introduced technique that allows attackers to perform arbitrary computation without injecting their code by reusing only the existing code fragments. Our external monitor is attached to the outside of the host system via the system bus and ARM CorSight PTM, and fed with execution traces of a victim application running on the host. As a majority of CRAs violates the normal execution behaviors of a program, our monitor constantly watches and analyzes the execution traces of the victim application and detect a symptom of attacks when the execution behaviors violate certain rules that normal applications are known to adhere. We present two different implementations for this purpose; a hardware-based solution in which all the CRA detection components are implemented in hardware, and a hardware/software mixed solution that can be employed in more resource constrained environment where the deployment of the full hardware level CRA detection is burdensome.

Accelerated Soft-Error-Rate (SER) Estimation for Combinational and Sequential Circuits

Radiation-induced soft errors have posed an increasing reliability challenge to combinational and sequential circuits in advanced CMOS technologies. Therefore, it is imperative to devise fast, accurate and scalable soft error rate (SER) estimation methods as part of cost-effective robust circuit design. This paper presents an efficient SER estimation framework for combinational and sequential circuits, which considers single-event transients (SETs) in combinational logic and multiple cell upsets (MCUs) in sequential elements. A novel top-down memoization algorithm is proposed to accelerate the propagation of SETs, and a general schematic and layout co-simulation approach is proposed to model the MCUs for redundant sequential storage structures. The feedback in sequential logic is analyzed with an efficient time frame expansion method. Experimental results on various ISCAS85 combinational benchmark circuits demonstrate that the proposed approach achieves up to 560.2X times speedup with less than 3\% difference in terms of SER results compared with the baseline algorithm. The average runtime of the proposed framework on a variety of ISCAS89 sequential benchmark circuits is 2.535s, and the runtime is 30.429s for the largest benchmark circuit with more than 1,000 flip-flops and 20,000 gates.

Efficient Mapping of Applications for Future Chip-Multiprocessors in Dark-Silicon Era

The failure of Dennard scaling has led to the utilization wall that is the source of dark silicon and limits the percentage of a chip that can actively switch within its power budget. To address this issue, a structure is needed to guarantee the limited power budget along with providing sufficient flexibility and performance for different applications with various communication requirements. In this line, we present a general-purpose platform for future many-core Chip-Multiprocessors (CMPs) which benefits from the advantages of clustering, Network-on-Chip (NoC) resource sharing among cores, and power gating the unused components of clusters. We also propose two task mapping methods for the proposed platform in which active and dark cores are dispersed appropriately so that an excess of power budget can be obtained. Our evaluations reveal that the first and second proposed mapping mechanisms respectively reduce the execution time by up to 28.6% and 39.2%, the NoC power consumption by up to 11.1% and 10%, and gain an excess power budget of up to 7.6% and 13.4%, over the baseline architecture.

Content-Aware Bit Shuffling for Maximizing PCM Endurance

Recently, phase change memory (PCM) is emerging as a strong replacement for DRAM owing to its many advantages such as non-volatility, high scalability, and so on. However, PCM is still restricted for use as main memory because of its limited write endurance. There have been many methods introduced to resolve the problem by reducing bit flips. Although they have significantly contributed to bit flip reduction, they still have the drawback that the lower bits are flipped more often than the higher bits. The reason is that these methods do not consider the fact that, in general, the lower bits are updated much more frequently than the higher bits. In this paper, we propose a noble content-aware bit shuffling (CABS) technique that minimizes bit flips and evenly distributes them to maximize the lifetime of PCM at the bit level. We also introduce two additional optimizations, namely, addition of an inversion bit and use of an XOR key, to further reduce bit flips. Moreover, CABS is capable of recovering from stuck-at faults by restricting the change in values of stuck-at cells. Experimental results showed that CABS outperformed the existing state-of-the-art methods in the aspect of PCM lifetime extension with minimal overhead. Specifically, CABS achieved up to 48.5% enhanced lifetime compared to the data comparison write (DCW) method, while consuming a few extra resources for metadata. We have also confirmed that CABS is fully applicable to BCH codes as it was able to reduce the maximum number of bit flips in metadata cells by 32.1%.

CDTA: A Comprehensive Solution for Counterfeit Detection, Traceability and Authentication in IoT Supply Chain

The Internet of Things (IoT) is transforming the way we live and work by increasing the connectedness of people and things on a scale that was once unimaginable. However, the vulnerabilities in IoT supply chain have raised serious concerns about the security and trustworthiness of IoT devices and components on them. Testing for device provenance, detection of counterfeit integrated circuits (ICs) and systems, and traceability of IoT devices are challenging issues to address. In this paper, we develop a novel RFID-based system suitable for Counterfeit Detection, Traceability and Authentication in IoT supply chain called CDTA. CDTA is composed of different types of on-chip sensors and in-system structures that collect necessary information to detect multiple counterfeit IC types (recycled, cloned, etc.), track and trace IoT devices, and verify the overall system authenticity. Central to CDTA is an RFID tag employed as storage and a channel to read the information from different types of chips on the printed circuit board (PCB) in both power-on and power-off scenarios. A novel board ID generator is implemented by combining outputs of physical unclonable functions (PUFs) embedded in RFID tag and different chips on the PCB. A light-weight RFID protocol is proposed to enable mutual authentication between RFID readers and tags. We also implement a secure inter-chip communication on the PCB. Simulations and experimental results using Spartan 3E FPGAs demonstrate the effectiveness of this system. The efficiency of the radio frequency (RF) communication has also been verified via a PCB prototype with a printed slot antenna.

Temperature Effect Inversion Aware Dynamic Thermal Management for FinFET Circuits

Due to the superb characteristics, FinFETs have emerged as a promising replacement for planar CMOS devices in sub-20nm CMOS technology nodes. However, based on extensive simulations, we have observed that the gate delay vs. temperature characteristics of FinFET circuits may be fundamentally different from that of the conventional bulk CMOS circuits, i.e., the delay of a FinFET circuit decreases with increasing temperature even in the super-threshold supply voltage regime. Fur- thermore, with the optimal buffer insertion, we have observed that interconnect delay of the FinFET circuits may follow the same trend for the temperature change. Unfortunately, the leakage power dissipation of the FinFET-based circuits increases exponentially with the temperature. These two trends give rise to a tradeoff between delay and leakage power as a function of the chip temperature, and hence, lead to the definition of an optimum chip temperature operating point (i.e., one that balances concerns about the circuit speed and power efficiency.) This paper presents the results of our investigations into the aforesaid temperature effect inversion (TEI) and proposes a novel dynamic thermal management (DTM) algorithm, which exploits this phenomenon to minimize the energy consumption of FinFET circuits without any appreciable performance penalty. Experi- mental results demonstrate that significant energy saving (as high as 36%, with no performance penalty) can be achieved by the proposed TEI-aware DTM approach compared to the best-in-class DTMs that are unaware of this phenomenon.

Design Methodology of Fault-Tolerant Custom 3D Network-on-Chip

A systematic design methodology is presented for custom Network-on-Chip (NoC) in three-dimensional integrated circuits (3D-ICs). In addition, fault tolerance is supported in the NoC if extra links are included in the NoC topology. In the proposed method, processors and the communication architecture are synthesized simultaneously in the 3D floorplanning process. 3D-IC technology enables ICs to be implemented in smaller size with higher performance; on the flip side, 3D-ICs suffer yield loss due to multiple dies in a 3D stack and lower manufacturing yield of through-silicon vias (TSVs). To alleviate this problem, KGD test can be applied to ensure every die to be packaged into a 3D-IC is fault-free. However, faulty TSVs cannot be tested in the KGD test. In this paper, the proposed method deals with the problem by providing fault-tolerance in the NoC topology. The efficiency of the proposed method is evaluated using several benchmark circuits, and the experimental results show that the proposed method produces 3D NoCs with comparable performance than previous methods when fault tolerant features are not realized. With fault tolerance in NoCs, higher yield can be achieved at the cost of performance penalty and elevated power level.

Parallel High-Level Synthesis Design Space Exploration for Behavioral IPs of Exact Latencie

This works presents a Design Space Exploration (DSE) method for Behavioral IPs (BIPs) given in ANSI-C or SystemC in order to find the smallest micro-architecture for a specific target latency. Previous work on High-Level Synthesis (HLS) DSE mainly focused on finding a trade-off curve with Pareto-optimal designs. HLS is however a single process (component) synthesis method. Very often, the latency of the components requires a specific fixed latency when inserted within a larger system. This work presents a fast multi-threaded method to find the smallest micro-architecture for a given BIP and target latency, by discriminating between all different exploration knobs and exploring these concurrently. Experimental results shows that our propose method is very effective and comprehensive results compare the quality of results vs. the speedup of your proposed explorer.

Automated Integration of Dual-Edge Clocking for Low-Power Operation in Nanometer Nodes

Clocking power, including both clock distribution and registers, has long been one of the primary factors in the total power consumption of many digital systems. One straightforward approach to reduce this power consumption is to apply dual-edge triggered (DET) clocking, since sequential elements operate at half the clock frequency, while maintaining same throughput as with conventional single-edge triggered (SET) clocking. However, the DET approach is rarely taken in modern integrated circuits, primarily due to the perceived complexity of integrating such a clocking scheme. In this paper, we first identify the most promising conditions for achieving low-power operation with DET clocking, and then introduce a fully automated design flow for applying DET to a conventional SET design. The proposed design flow is demonstrated on three benchmark circuits in a 40 nm CMOS technology, providing as much as a 50% reduction in clock distribution and register power consumption.


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First Name Last Name Award
Iris Bahar ACM Distinguished Member (2012)
Robert Brayton ACM Paris Kanellakis Theory and Practice Award (2006)
Krishnendu Chakrabarty ACM Distinguished Member (2008)
ACM Senior Member (2006)
Naehyuck Chang ACM Distinguished Member (2012)
ACM Senior Member (2007)
Danny Z Chen ACM Distinguished Member (2014)
ACM Senior Member (2011)
Nikil D. Dutt ACM Distinguished Member (2007)
Franz Franchetti ACM Senior Member (2015)
ACM Gordon Bell Prize (2006)
Soheil Ghiasi ACM Senior Member (2015)
Prosenjit Gupta ACM Senior Member (2008)
Matthew Guthaus ACM Senior Member (2013)
Pao-Ann Hsiung ACM Senior Member (2006)
Mary Jane Irwin ACM Athena Lecturer Award (2010)
ACM Distinguished Service Award (2005)
John Lee ACM Senior Member (2014)
Diana Marculescu ACM Distinguished Member (2011)
ACM Senior Member (2009)
Igor Markov ACM Distinguished Member (2011)
ACM Senior Member (2007)
Sally A McKee ACM Senior Member (2013)
Prabhat Mishra ACM Distinguished Member (2015)
ACM Senior Member (2010)
Saraju P. Mohanty ACM Senior Member (2010)
Trevor Mudge ACM-IEEE CS Eckert-Mauchly Award (2014)
Walid Najjar ACM Distinguished Member (2015)
ACM Senior Member (2014)
Steven M Nowick ACM Senior Member (2009)
Ian Parberry ACM Distinguished Member (2015)
Massoud Pedram ACM Distinguished Member (2008)
Sreeranga P Rajan ACM Distinguished Member (2014)
Bantwal R Rau ACM-IEEE CS Eckert-Mauchly Award (2002)
Sartaj K Sahni ACM Karl V. Karlstrom Outstanding Educator Award (2003)
Robert Schreiber ACM Distinguished Member (2006)
Sandeep K Shukla ACM Distinguished Member (2012)
ACM Senior Member (2007)
Anand Sivasubramaniam ACM Distinguished Member (2010)
ACM Senior Member (2009)
Peter James Stuckey ACM Distinguished Member (2009)
Mateo Valero ACM Distinguished Service Award (2012)
ACM-IEEE CS Eckert-Mauchly Award (2007)
Robert A. Walker Outstanding Contribution to ACM Award (2007)
ACM Distinguished Member (2006)
David Whalley ACM Distinguished Member (2009)
ACM Senior Member (2009)
Steve Wilton ACM Senior Member (2006)
Zeljko Zilic ACM Senior Member (2009)

First Name Last Name Paper Counts
Francky Catthoor 18
Irith Pomeranz 15
Nikil Dutt 15
Krishnendu Chakrabarty 13
Jason Cong 12
Sheldon Tan 10
Partha Chakrabarti 10
TingTing Hwang 9
Sachin Sapatnekar 9
Lei He 8
Yaowen Chang 8
Spyros Tragoudas 7
Yunheung Paek 7
Evangeline Young 7
Frank Vahid 7
Pallab Dasgupta 7
Massoud Pedram 7
Danny Wong 7
Luca Benini 7
Taewhan Kim 6
Martin Wong 6
Alexandru Nicolau 6
John Hayes 6
Bhargab Bhattacharya 6
Ryan Kastner 6
Chengkok Koh 6
Radu Marculescu 6
Sudhakar Reddy 6
Igor Markov 6
Ali Dasdan 5
Sule Ozev 5
Sharad Malik 5
David Pan 5
Kiyoung Choi 5
Ramesh Karri 5
Kaushik Roy 5
Mahmut Kandemir 5
Umit Ogras 5
Soonhoi Ha 5
Jenqkuen Lee 5
Preeti Panda 5
Rajeev Kumar 5
Aviral Shrivastava 5
Giovanni De Micheli 5
Andrew Kahng 5
Tony Givargis 5
Nagarajan Ranganathan 5
Roman Lysecky 5
Chungkuan Cheng 5
Kwangting Cheng 4
Rajesh Gupta 4
Zijiang Yang 4
Sunil Khatri 4
Chialin Yang 4
El Aboulhamid 4
Jingyang Jou 4
Aarti Gupta 4
Xiaobosharon Hu 4
Pinghung Yuh 4
Shihhsu Huang 4
Peter Petrov 4
Peng Li 4
Iris Jiang 4
Alex Jones 4
Yuanhao Chang 4
Hungming Chen 4
Sunyuan Hsieh 4
Hans Wunderlich 4
Chang Liu 4
Jintai Yan 4
Allen Wu 4
Naehyuck Chang 4
Miodrag Potkonjak 4
Paul Gratz 4
Jongeun Lee 4
Dinesh Mehta 4
Franco Fummi 4
Paulo Flores 4
Hai Zhou 4
Dirk Stroobandt 4
Zonghua Gu 4
Azadeh Davoodi 4
Shihchieh Chang 3
Xianlong Hong 3
Greg Stitt 3
Li Wang 3
Chakkuen Wong 3
Waikei Mak 3
Seda Memik 3
Yuan Xie 3
Karel Bruneel 3
Henk Corporaal 3
Dimitrios Kagaris 3
Bijan Alizadeh 3
Praveen Raghavan 3
Martin Lukasiewycz 3
Valeria Bertacco 3
Viktor Prasanna 3
Diana Marculescu 3
Jürgen Teich 3
Ronald Blanton 3
Zili Shao 3
Ozgur Sinanoglu 3
Paolo Prinetto 3
Sebastian Steinhorst 3
Paoann Hsiung 3
Sreejit Chakravarty 3
Wen Jone 3
Guangming Wu 3
Axel Jantsch 3
Alain Girault 3
Janet Roveda 3
Guy Gogniat 3
Sisira Panda 3
Zoran Salcic 3
Dipankar Das 3
Prabhat Mishra 3
Masanori Kurimoto 3
Yuchin Hsu 3
Xiaoyu Song 3
Yunsi Fei 3
Anna Bernasconi 3
Ozcan Ozturk 3
Arnout Vandecappelle 3
Chenjie Yu 3
Costas Goutis 3
Peter Cheung 3
Youngsoo Shin 3
Shiyu Huang 3
Chungwen Huang 3
Karem Sakallah 3
Valentina Ciriani 3
Alberto Sangiovanni-Vincentelli 3
Mehdi Tahoori 3
Juan Maestro 3
Massimo Poncino 3
Fadi Kurdahi 3
Partha Roop 3
Tsungyi Ho 3
Seongnam Kwon 3
Gianpiero Cabodi 3
Soheil Ghiasi 3
Pai Chou 3
Sarma Vrudhula 3
Kurt Keutzer 3
Thambipillai Srikanthan 3
Yowtyng Nieh 3
Martin Palkovič 3
Daniel Gajski 3
Pedro Reviriego 3
Xiangrong Zhou 3
Yi Wang 3
Madhu Mutyam 3
David Atienza 3
Majid Sarrafzadeh 3
Per Kjeldsberg 3
Janak Patel 3
José Monteiro 3
Baris Taskin 3
Hai Wang 3
Chiuwing Sham 3
Edwin Sha 3
Domenic Forte 3
Dong Xiang 3
Yinhe Han 3
Nicholas Zamora 3
Saojie Chen 3
Priyank Kalla 3
Elizabeth Rudnick 3
Yiping You 3
Enrico Macii 3
Ankur Srivastava 3
Shuvra Bhattacharyya 3
Krishnendu Chakrabarty 3
Twan Basten 3
Teiwei Kuo 3
Hao Yu 3
George Constantinides 3
Murali Jayapala 2
Javed Absar 2
Lei Li 2
Krzysztof Kuchcinski 2
Yvon Savaria 2
Xin Yuan 2
Peng Li 2
Shmuel Wimer 2
Rafal Baranowski 2
Bin Liu 2
Kaihui Chang 2
Pochun Huang 2
Bocheng Lai 2
José Güntzel 2
Sandeep Shukla 2
Xin Li 2
Eduard Cerny 2
Jun Gu 2
Poyuan Chen 2
Junji Sakai 2
Abhijit Jas 2
Jaume Abella 2
Sungmo Kang 2
Junjuan Xu 2
Vasilios Kelefouras 2
David Hély 2
Sungjoo Yoo 2
Sunggu Lee 2
Chandra Suresh 2
Melvin Breuer 2
Marco Murciano 2
Xiaoping Hu 2
Manfred Glesner 2
Jim Holt 2
Magdy Abadir 2
Adnan Aziz 2
Saraju Mohanty 2
Tajana Rosing 2
Željko Žilić 2
Chunjason Xue 2
Michael Riepe 2
Stefano Quer 2
Mohammad Tehranipoor 2
Luiz Dos Santos 2
Ranga Vemuri 2
Mehrdad Nourani 2
Kai Zhu 2
ChengHsing Yang 2
Nur Touba 2
Hyesoon Kim 2
Elaheh Bozorgzadeh 2
Hongbing Fan 2
Shantanu Dutt 2
Paul Bogdan 2
Hiren Patel 2
Pascal Fradet 2
Radu Marculescu 2
Puneet Gupta 2
Hsinhung Chen 2
Yongje Lee 2
Jinyong Lee 2
Qing Duan 2
Jos Huisken 2
Chiaming Chang 2
Donald Thomas 2
S Ramesh 2
Francisco Cazorla 2
Matteo Reorda 2
Guido Araújo 2
Fei Su 2
Wayne Luk 2
P Chakrabarti 2
Matthew Guthaus 2
Gustavo Wilke 2
Julien Schmaltz 2
Markus Püschel 2
Doosan Cho 2
Jingyang Jou 2
Vinícius Livramento 2
Francesco Poletti 2
Miguel Miranda 2
Mary Irwin 2
Ingoo Heo 2
Marlin Mickle 2
Hiroaki Inoue 2
Kanupriya Gulati 2
Sudip Roy 2
Luís Silveira 2
Vivek Sarin 2
Ali Afzali-Kusha 2
Deming Chen 2
José Mendías 2
Ronald Graham 2
Yiyu Liu 2
M Balakrishnan 2
Stan Liao 2
Mike Lee 2
Ansuman Banerjee 2
Sreeranga Rajan 2
Avinoam Kolodny 2
Hsiangpang Li 2
Michael Kochte 2
Erik Marinissen 2
Genggeng Liu 2
Wenzhong Guo 2
Meeta Srivastav 2
Bart Mesman 2
Muhammet Ozdal 2
Samarjit Chakraborty 2
Bei Yu 2
Peiwen Luo 2
Dawei Chang 2
Shenchih Tung 2
Mario López 2
Kun Yuan 2
Arcot Sowmya 2
Rajdeep Mukhopadhyay 2
Yiyu Shi 2
Peichen Pan 2
Chung Tsao 2
Kees Goossens 2
Chinhsien Wu 2
Chao Wang 2
Meikang Qiu 2
Masato Edahiro 2
Angeliki Kritikakou 2
Aiqun Cao 2
Roberto Passerone 2
Luciano Lavagno 2
Michel Auguin 2
Min Xu 2
Vijaykrishnan Narayanan 2
Freek Verbeek 2
Michael Hsiao 2
Xuexin Liu 2
Anmol Mathur 2
Sergio Nocco 2
Zhiyu Zeng 2
Dongsheng Ma 2
Chiajui Hsu 2
José Pino 2
Jochen Jess 2
JoAnn Paul 2
Konstantin Moiseev 2
Jun Yang 2
Luigi Carro 2
Chingren Lee 2
Dakai Zhu 2
Leyla Nazhandali 2
Gregory Dimitroulakos 2
Akash Kumar 2
Timothy Sherwood 2
Swaminathan Narayanaswamy 2
Adnan Bouakaz 2
Haibo Zeng 2
Chienchih Huang 2
Chinlong Wey 2
Jwu Chen 2
Shihhao Hung 2
Wayne Wolf 2
Graziano Pravadelli 2
John Gough 2
Hai Wang 2
Mateo Valero 2
Avinash Malik 2
Jörg Henkel 2
Swarup Bhunia 2
Susmita Sur-Kolay 2
Guangyu Chen 2
Paul Thadikaran 2
Marc Boulé 2
Younlong Lin 2
C Shi 2
Yiyu Shi 2
Arnab Roy 2
Laungterng Wang 2
Xing Huang 2
Peter Milder 2
Hui Liu 2
Guihai Yan 2
Ricardo Reis 2
Siddharth Garg 2
Nicola Bombieri 2
Jiping Liu 2
Maria Michael 2
Mohammad Arjomand 2
Bo Zhao 2
Sujit Dey 2
James Cain 2
Leonid Mats 2
Marco Bekooij 2
Franjo Ivančić 2
Zhiwei Qin 2
Mark Tehranipoor 2
Kiwook Kim 2
Maurizio Rebaudengo 2
Russell Tessier 2
Kyumyung Choi 2
Srinivas Devadas 2
Vigyan Singhal 2
Ismail Kadayif 2
Levent Aksoy 2
Smita Bakshi 2
Siddhartha Mukhopadhyay 2
Rudy Lauwereins 2
Srinivas Katkoori 2
Andreas Dandalis 2
Guolong Chen 2
Janming Ho 2
Sudhakar Yalamanchili 2
Qinru Qiu 2
Deepak Mathaikutty 2
Robert Walker 2
Ayse Coskun 2
Sanghamitra Roy 2
Haibao Chen 2
Gary Dispoto 2
Jun Yang 2
Natarajan Viswanathan 2
Román Hermida 2
Tsungyi Ho 2
Picheng Hsiu 2
Cheng Wang 2
Christophe Wolinski 2
Alper Sen 2
Yongjoo Kim 2
Wim Heirman 2
Dimitrios Soudris 2
Zebo Peng 2
Sivaram Gopalakrishnan 2
Jagannathan Ramanujam 2
Erik Brockmeyer 2
Inki Hong 2
Duncan Walker 2
Farinaz Koushanfar 2
Naiwen Chang 2
Masahiro Fujita 2
Chiachun Tsai 2
Chrystian Guth 2
Yuliang Wu 2
Jhihrong Gao 2
Seokhyeong Kang 2
Sarmishtha Ghoshal 2
Hafizur Rahaman 2
Koushik Chakraborty 2
Jin Sun 2
Jun Zeng 2
Swapna Dontharaju 2
Mahir Turkcan 1
Deming Chen 1
Jaekyu Lee 1
Kumar Parthasarathy 1
Pablo Del Valle 1
Giacomo Paci 1
YoungMin Yi 1
Tathagato Dastidar 1
Mohamed Bechara 1
Pinhong Chen 1
Lingling Jin 1
Nikhil Saluja 1
Shakith Fernando 1
Jeff White 1
Adam Postula 1
Anuja Sehgal 1
Frank Hannig 1
Yu Cao 1
Karthik Shankar 1
Song Liu 1
Ge Yu 1
Javier Resano 1
Daniel Mozos 1
KuangCyun Hsiao 1
Jason Higgins 1
Peter Marwedel 1
Saurabh Adya 1
Kiyin Chang 1
Ian Parberry 1
Chichou Kao 1
Heman Khanna 1
David Long 1
Mahesh Iyer 1
Yehia Massoud 1
Qingfeng Zhuge 1
Sunil Chappidi 1
Hyunggyu Lee 1
Jongman Kim 1
Celina Val 1
Sumit Mohanty 1
Gang Quan 1
CP Ravikumar 1
Jay Roy 1
Suman Datta 1
Ujjwal Guin 1
Peixin Li 1
WeiChung Chao 1
Chang Xu 1
Andrew Kennings 1
Xiaoqing Xu 1
Wenchao Zhang 1
Shengxi Diao 1
Pangbo Wu 1
Ramachandran Venkatasubramanian 1
Hazem Ali 1
Ioannis Latifis 1
Christakis Lezos 1
Maria García 1
Marc Heijligers 1
Weitong Chuang 1
Einar Aas 1
Sagar Sabade 1
Xiaoping Tang 1
Jaehwanjohn Lee 1
Subhankar Mukherjee 1
Pallab Dasgupta 1
Ruijing Shen 1
Diederik Verkest 1
David Kolson 1
Kuochen Wang 1
Jun Chen 1
Hakan Yalcin 1
Franck Yonga 1
Ling Li 1
Yunji Chen 1
Chinchi Teng 1
Chibang Kuan 1
Phillip Jones 1
Ahcène Bounceur 1
Jinnshyan Wang 1
Chengyang Fu 1
ChengTsung Hwang 1
Sudhakar Muddu 1
Xiaoyao Liang 1
Alan Mishchenko 1
Shichun Tsai 1
Qiang Dou 1
Luis Bathen 1
Chienchin Huang 1
Suming Lai 1
Dionisios Pnevmatikatos 1
Dirk Muller 1
Hao Shen 1
Nadereh Hatami 1
Reeshav Kumar 1
Selvaraj Ravi 1
Reinhard Schneider 1
Peng Li 1
Mohammed Ehteshamuddin 1
Jian Liu 1
Heejong Park 1
Qi Zhang 1
Sara Vinco 1
Vinay Verma 1
PoHsien Chang 1
Gabriela Nicolescu 1
Swaroop Ghosh 1
QingPing Tan 1
Jinfeng Liu 1
Maurice Bruynooghe 1
Karam Chatha 1
Mukund Narasimhan 1
Naran Sirisantana 1
Alex Yakovlev 1
Yinlong Xu 1
Christoph Kern 1
Zhaoliang Pan 1
Wei Zhao 1
Hungyi Li 1
Vladimir Zolotov 1
Stefano Quer 1
Henrik Esbensen 1
Sreejit Chakravarty 1
Li Shang 1
Zhuo Feng 1
Santiago Rodríguez 1
Huawei Li 1
Sanghyeon Baeg 1
Weitsun Sun 1
Sungkyu Lim 1
Kunhyuk Kang 1
Jason Cheatham 1
Mauricio Ayala-Rincón 1
Hannahhonghua Yang 1
Qiang Zhou 1
Paul Pop 1
Traian Pop 1
Petru Eles 1
Gunar Schirner 1
Andreas Gerstlauer 1
Swanwa Liao 1
Xue Liu 1
Somnath Paul 1
Yuan Cai 1
Ricardo Reis 1
Chincheng Kuo 1
Éamonn Linehan 1
Chandan Karfa 1
Xiaojian Yang 1
Stefan Obenaus 1
Fabrizio Lombardi 1
Bruno Girodias 1
Youcef Bouchebaba 1
Thomas Parnell 1
Sudipta Bhawmik 1
Justin Stander 1
Frederik Vandeputte 1
Stelios Mamagkakis 1
Puneet Sharma 1
Arnab Sinha 1
Bhaskar Pal 1
Yuanfang Hu 1
Yubin Zhang 1
Adam Hartman 1
Huihsin Hsu 1
Jenhao Chen 1
Douglas Keller 1
Jongkyung Paek 1
Enshou Chang 1
Daujieu Yang 1
Xu He 1
Yao Wang 1
Chi Zhang 1
Swarup Bhunia 1
Megha Gandhi 1
Arnab Sarkar 1
Giovanni Squillero 1
Ibrahim Hajj 1
Vikram Saxena 1
Francisco Fernández 1
Chihhung Liu 1
Syyen Kuo 1
Paul Feautrier 1
Yi Xu 1
Vincent Beroulle 1
Kele Shen 1
Zhi Li 1
Mehdi Kamal 1
Viktor Lapinskii 1
Gustavo De Veciana 1
Xiaobosharon Hu 1
Xiaofang Wang 1
Filipa Duarte 1
Jun Zhou 1
Xinzhang Jia 1
Hsien Lee 1
Chen Li 1
Ricardo Jacobi 1
Zuoyuan Li 1
Kuohua Wang 1
J Chen 1
U Rovati 1
Ausif Mahmood 1
William Hung 1
Sumit Gupta 1
Stephen Cauley 1
Ying Hu 1
Yufu Zhang 1
Stephen Edwards 1
Seongook Jung 1
Ali Pınar 1
Jackey Yan 1
Chris Chu 1
Yongwen Wang 1
Dominik Erb 1
Matthias Sauer 1
Tobias Schubert 1
Minseok Kang 1
Baktash Boghrati 1
Hai Wang 1
Tim Nieberg 1
José Costa 1
Ying Tan 1
Gwan Choi 1
Dacheng Juan 1
Diana Marculescu 1
Dip Goswami 1
Haotse Chen 1
Linzhang Wang 1
Namita Sharma 1
Jean Desbarbieux 1
Emmanuelle Encrenaz 1
Safar Hatami 1
Ganghee Lee 1
Zheng Xu 1
Marc Geilen 1
Giorgio Natale 1
Qiang Ma 1
Martin Wong 1
Sanghyun Park 1
Yongjoo Kim 1
Yahya Osais 1
Markus Seuring 1
Randall Geiger 1
Degang Chen 1
Hamid Shojaei 1
Youtao Zhang 1
Yaolin Chang 1
Tero Rissa 1
Chris Bleakley 1
Hidehiro Takata 1
Yosinori Watanabe 1
Renshen Wang 1
Anshul Kumar 1
Swarup Das 1
Michael Münch 1
Laurent Freund 1
Mohammad Foroozannejad 1
Hassan Salamy 1
J Lee 1
Giri Tiruvuri 1
Franc Breglez 1
Michael Gasteier 1
W Fuchs 1
Ismed Hartanto 1
Kuangchien Chen 1
Koen Danckaert 1
Steven Levitan 1
Noureddine Chabini 1
Hsiangyu Lu 1
Yiran Chen 1
Bernd Wurth 1
Ulf Schlichtmann 1
Olivier Sentieys 1
Pai Chou 1
Saket Gupta 1
Sartaj Sahni 1
Anjur Krishnakumar 1
Jiang Hu 1
Vilasita Kuntamukkala 1
Steve Tjiang 1
Nagu Dhanwada 1
Andrew Cassidy 1
Hua Xiang 1
Arijit Mondal 1
Xiaoqing Wen 1
Xiaoqing Yang 1
Yuliang Wu 1
Bert Geelen 1
Jaehyun Kim 1
Rajeev Rao 1
David Van Campenhout 1
Hussain Al-Asaad 1
Dinesh Ramanathan 1
Pinar Korkmaz 1
Yan Lin 1
Raymond Hoare 1
John Lockwood 1
Sabyasachi Das 1
Krste Asanović 1
Huaizhi Wu 1
Sudarshan Bahukudumbi 1
Kundan Nepal 1
Francesco Zanini 1
Colin Jones 1
Naifeng Jing 1
Santiago Mok 1
Chaohung Lu 1
Jarrod Roy 1
Nan Guan 1
Carlos González 1
Andrea Calimera 1
Thorlindur Thorolfsson 1
B Rau 1
Mohammad Tehranipour 1
Edwin Naroska 1
ZoltánÁdám Mann 1
Jamil Kawa 1
Dhananjay Kulkarni 1
Edwin Sha 1
Yehchi Chang 1
Gregor Goessler 1
Wei Hu 1
Chia Yen 1
Mohammed Elshoukry 1
Hongliang Chang 1
Laurence Goodby 1
Luís Guerra E Silva 1
Shi Lin 1
Ramin Fallahzadeh 1
Hongfei Wang 1
Fubing Mao 1
Hai Li 1
Hosoon Shin 1
Qihang Shi 1
Wei Zhong 1
Chuangwen Liu 1
Benny Åkesson 1
Yejyun Lin 1
Jonathan Martin 1
Rina Panigrahy 1
Hao Li 1
Vijay Sundararajan 1
Juan Lanchares 1
Rajiv Gupta 1
Christophe Bobda 1
Tianshi Chen 1
Depei Qian 1
Hungsheng Chang 1
Salvador Mir 1
E Mariatos 1
Hsinhung Lin 1
Yoshiaki Fukui 1
YannRue Lin 1
Yihlang Li 1
Mohamed Zahran 1
Douglas Myers 1
Robert Brayton 1
Jonghee Youn 1
Yuan Yuan 1
Christian Hochberger 1
Alexander Weiss 1
Christian Panten 1
Unmesh Bordoloi 1
Petru Eles 1
Yoan Lin 1
Marcelo Johann 1
Qiuping Yi 1
Zili Shao 1
Dhiraj Pradhan 1
Chaowen Tzeng 1
Joachim Anlauf 1
Kueichung Chang 1
Jihsheng Shen 1
Sami Taktak 1
Jianli Zhuo 1
Xingguang Feng 1
Dongwoo Lee 1
Jonghee Yoon 1
Ahmed Abousamra 1
Dirk Niggemeyer 1
Yiran Chen 1
Pu Liu 1
Bilge Akgul 1
Tsuangwei Chang 1
Hyunggyu Lee 1
David Kidd 1
Scott Van Sooy 1
Vijay Pitchumani 1
Ivan Hom 1
Gert Goossens 1
Dirk Lanneer 1
Joan Carletta 1
Mehrdad Nourani 1
Teemu Pitkänen 1
Hirofumi Shinohara 1
Marcus Schmitz 1
Bashir Al-Hashimi 1
Zhanglei Wang 1
Cécile Belleudy 1
Xiaoke Qin 1
Jayanta Bhadra 1
John Pape 1
Eren Kursun 1
Siobhán Clarke 1
Hongting Lin 1
Padmaraj Singh 1
ThuydM Le 1
Trongyen Lee 1
Moonjung Chung 1
Wolfgang Rosenstiel 1
Bita Gorjiara 1
Nader Bagherzadeh 1
Dmitri Maslov 1
Gang Chen 1
François Boyer 1
Jeroen Voeten 1
João Marques-Silva 1
TaiHung Liu 1
Chauchin Su 1
Chidamber Kulkarni 1
Tim Kong 1
Abhijit Chatterjee 1
Andy Yan 1
Ra'ed Al-Dujaily 1
Raid Ayoub 1
Jason Tong 1
Weikai Cheng 1
Charalambos Ioannides 1
V Nair 1
Ashok Sudarsanam 1
Janet Wang 1
Alexandro Baldassin 1
James Moscola 1
Young Cho 1
Sudarshan Srinivasan 1
Jaehyun Park 1
Concepcion Sanz 1
Sotirios Xydis 1
George Economakos 1
Nicholas Imbriglia 1
Giovanni De Micheli 1
Sherief Reda 1
Takeshi Yamamoto 1
Satoshi Nakano 1
John Lee 1
Rajarshi Mukherjee 1
Martha Pollack 1
Rupak Majumdar 1
Giacomo Marchetti 1
Samson Melamed 1
Nikhil Jayakumar 1
Ahmad Al-Yamani 1
Koen Van Eijk 1
Qin Zhao 1
Yentai Lai 1
Michele Malgeri 1
Kumar Lalgudi 1
Marios Papaefthymiou 1
Maciej Ciesielski 1
Songra Pan 1
Graeme Gange 1
Alan Hu 1
Xiaowei Li 1
Cristiana Bolchini 1
Frédéric Vivien 1
Paul Chau 1
Chingyi Huang 1
Pascal Meinerzhagen 1
Adam Teman 1
Ramprasath S 1
Yichung Chen 1
Wei Zhang 1
Qing Dong 1
Renan Netto 1
Zhiliang Qian 1
Pejman Lotfi-Kamran 1
Mohammad Hosseinabady 1
Robert Schreiber 1
Meenakshi Kaul 1
Alex OrailoĞLu 1
Steffen Schlueter 1
Chinghsuan Ho 1
Chunyao Wang 1
Rickard Ewetz 1
Ya Wang 1
Yue Zhao 1
Kenneth Stevens 1
Seungwon Kim 1
Taemin Lee 1
Hyunsun Park 1
Junwhan Ahn 1
Hyunok Oh 1
Sparsh Mittal 1
Nitin Chandrachoodan 1
Qingbo Wu 1
Dongha Jung 1
Dimin Niu 1
William Robinson 1
Lei Jiang 1
Brahim Al Farisi 1
James Harbin 1
Jingwei Lu 1
Chulhong Park 1
Qinke Wang 1
Sayantan Das 1
Michael Taylor 1
Yenchun Lin 1
SueHong Chow 1
Eddie Hung 1
Karin Avnit 1
Sudeep Pasricha 1
Yuwei Wu 1
Ganesh Gingade 1
Qixiao Liu 1
Yuru Hong 1
Philippe Grosse 1
Yves Durand 1
Owen Farell 1
Guoqing Chen 1
Liang Chen 1
Yongpan Liu 1
Song Jin 1
David Westwick 1
Jian Kuang 1
Robert Elio 1
Sander Stuijk 1
Chuansheng Dong 1
Ludovic Apvrille 1
Renaud Pacalet 1
Debashri Roy 1
Debasis Mitra 1
Yunfeng Yang 1
El Bourennane 1
Cong Xu 1
Shimeng Yu 1
Stavros Hadjitheophanous 1
Yingchi Li 1
Mohammad Samavatian 1
Ran Wang 1
Robert Johnson 1
Anand Raghunathan 1
Joachim Falk 1
Stefan Gheorghita 1
Andreas Hansson 1
Prasenjit Basu 1
Sounil Biswas 1
Chiaheng Tu 1
Gustavo Tellez 1
Seongseok Seo 1
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Martin Leucker 1
Renjie Lee 1
Hakan Aydín 1
Wenpin Tu 1
Yoonseok Yang 1
Samarjit Chakraborty 1
Kyle Stegner 1
Chao Wang 1
Jongchul Lee 1
Zhonghai Lu 1
Adam Kaplan 1
Amit Singh 1
Jhengsyun Yang 1
Yushih Su 1
Tienfu Chen 1
F Johnson 1
Hsiangyun Cheng 1
Huahsin Yeh 1
Jinkyu Koo 1
Anupama Subramaniam 1
V Kamakoti 1
Seonwook Kim 1
Hai Zhou 1
Hu Chen 1
Seyed Miremadi 1
Ali Mirtar 1
Karel Heyse 1
Jiunin Guo 1
Hongfei Wang 1
Zhuo Li 1

Affiliation Paper Counts
Indian Institute of Management Calcutta 1
Nan-Tai Institute of Technology 1
Winbond Electronics Corporation 1
Kung Shan Institute of Technology 1
Macau University of Science and Technology 1
DoCoMo Communications Laboratories Europe GmbH 1
Yahoo Inc. 1
Institute for Information Industry Taiwan 1
Synopsys (India) Pvt. Ltd. 1
Mindspeed Technologies 1
FZI Research Computer Science Research Center Karlsruhe 1
Asyst Technologies, Inc. 1
Huawei Technologies Co., Ltd. 1
Zenasis Technologies, Inc. 1
Intel Technology India Pvt Ltd. 1
International Institute of Information Technology, Kolkata 1
Barcelona Supercomputing Center 1
Hitachi America, Ltd. 1
STMicroelectronics Ltd - Bristol 1
National Pingtung Institute of Commerce 1
Faraday Technology Corporation 1
Universite de Lyon 1
Intel Development Center, Israel 1
Toshiba America Research, Inc 1
Universite de Strasbourg 1
National Institute of Technology, Durgapur 1
Global Unichip 1
Sun Yat-Sen University 1
East China Normal University 1
North China Electric Power University 1
Russian Academy of Sciences 1
Bahcesehir University 1
Catholic University of Pelotas 1
Microsoft Research 1
University of Potsdam 1
Beijing University of Chemical Technology 1
University of Virginia 1
Indian Institute of Technology, Kanpur 1
University of Central Florida 1
National Chi Nan University 1
Chongqing University 1
Ecole Centrale Marseille 1
National Taiwan Ocean University 1
Lancaster University 1
Oak Ridge National Laboratory 1
Missouri University of Science and Technology 1
University of Maryland, Baltimore County 1
The University of North Carolina at Chapel Hill 1
Northrop Grumman corporation 1
Jundi Shapur University of Dezful 1
Rensselaer Polytechnic Institute 1
Valparaiso University 1
University of Udine 1
Clarkson University 1
University of Nebraska - Lincoln 1
Royal Military College of Canada 1
School of Higher Technology - University of Quebec 1
San Francisco State University 1
Oracle Corporation 1
National Ilan University Taiwan 1
St. Louis University 1
Siemens AG 1
Daegu University 1
Wuhan University 1
Karlsruhe Institute of Technology, Campus South 1
Kent State University 1
Texas State University-San Marcos 1
Rutgers, The State University of New Jersey 1
Nortel Networks 1
Institute of Computing Technology Chinese Academy of Sciences 1
University of California System 1
Curtin University of Technology, Perth 1
McMaster University 1
Saint Francis Xavier University 1
University at Buffalo, State University of New York 1
University of Akron 1
North Dakota State University 1
University of Bridgeport 1
Miami University Oxford 1
Griffith University 1
Naval Postgraduate School 1
Concordia University, Montreal 1
Federal University of Santa Maria 1
University of Idaho 1
Gonzaga University 1
Texas Instruments (India) Ltd 1
Lahore University of Management Sciences 1
Hynix Semiconductor Inc. 1
Lebanese American University 1
P. A. College of Engineering 1
International Medical Equipment Collaborative 1
University of Colorado at Boulder 1
Wilfrid Laurier University 1
Mississippi State University 1
Florida State University 1
France Telecom 1
University of Manchester 1
Universite de Bretagne-Sud 1
China National Petroleum Corporation 1
University of Ioannina 1
Fu Jen Catholic University 1
Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas 1
Ecole Normale Superieure de Lyon 1
Google Inc. 1
Spanish National Research Council 1
City University of New York 1
Lawrence Berkeley National Laboratory 1
Thomson, SA 1
Cornell University 1
Commissariat a L'Energie Atomique CEA 1
University of Kansas 1
Colorado State University 1
Silicon Graphics, Inc. 1
Tampere University of Technology 1
University of St. Thomas, Minnesota 1
University of Kaiserslautern 1
Nanjing University of Science and Technology 1
Samsung Group 1
University of Kent 1
Auburn University 1
Oakland University 1
INRIA Rhone-Alpes 1
Qualcomm Incorporated 1
Czech Technical University in Prague 1
INRIA Institut National de Rechereche en Informatique et en Automatique 1
Oregon State University 1
Kwangwoon University 1
Indian Institute of Technology, Bombay 1
Providence University Taiwan 1
Oxford Brookes University 1
Kettering University 1
University of Southern California, Information Sciences Institute 1
North Carolina Agricultural and Technical State University 1
Robert Bosch GmbH 1
University of Trento 1
Chengdu University of Information Technology 1
Washington State University Tri-Cities 1
National Taipei University 1
University of New Brunswick 1
The University of North Carolina System 1
Vienna University of Technology 1
University of South Carolina 1
Sogang University 1
Technical University of Dresden 1
Bowling Green State University 1
Advanced Micro Devices, Inc. 1
LSI Corporation 1
Taiwan Semiconductor Manufacturing Company 1
Memorial University of Newfoundland 1
CSIC - Instituto de Investigacion en Inteligencia Artificial 1
Air Force Research Laboratory 1
State University of Rio Grande do Sul 1
United States Air Force Institute of Technology 1
Capital Normal University China 1
University of Twente 1
Villanova University 2
Virginia Commonwealth University 2
Polytechnic University - Brooklyn 2
Bar-Ilan University 2
Hefei University of Technology 2
Illinois Institute of Technology 2
Vanderbilt University 2
Mentor Graphics Corporation 2
Feng Chia University 2
University of Houston 2
Altera Corporation 2
CNRS Centre National de la Recherche Scientifique 2
Silesian Polytechnic University, Gliwice 2
King Fahd University of Petroleum and Minerals 2
Xilinx Inc. 2
Washington University in St. Louis 2
Kyushu University 2
IBM Research 2
National Sun Yat-Sen University Taiwan 2
Japan Advanced Institute of Science and Technology 2
National Taipei University of Technology 2
Beihang University 2
Brno University of Technology 2
University of Cantabria 2
University of Denver 2
University of Washington, Seattle 2
University of York 2
Radboud University Nijmegen 2
Michigan Technological University 2
University of Tubingen 2
Southern Methodist University 2
Washington State University Pullman 2
Wright State University 2
George Mason University 2
Binghamton University State University of New York 2
Technical University of Crete 2
Osaka University 2
Southern Illinois University 2
Open University of the Netherlands 2
University of Ferrara 2
University of Lethbridge 2
University of Southampton 2
University of Tokyo 2
Xidian University 2
Nokia Corporation 2
Universidad Autonoma de Madrid 2
University of Oxford 2
Institute for Research in IT and Random Systems 2
NXP Semiconductors 2
Lund University 2
National Semiconductor Corporation 2
Columbia University 2
Universite d' Evry Val d'Essonne 2
Infineon Technologies AG 2
Democritus University of Thrace 2
University of Queensland 2
Michigan State University 2
Indian Institute of Technology Roorkee 2
American University of Beirut 2
Cyprus University of Technology 2
National Key Laboratory for Parallel and Distributed Processing 2
Realtek Semiconductor Corp. 2
Avant Corporation 2
Case Western Reserve University 3
Catholic University of Louvain, Louvain-la-Neuve 3
Electronics Telecommunication Research Institute 3
University of Victoria 3
University of Texas at San Antonio 3
University of Arkansas - Fayetteville 3
Korea University 3
Bogazici University 3
Delft University of Technology 3
Kitakyushu University 3
The University of Hong Kong 3
University of Catania 3
University of Dublin, Trinity College 3
Bilkent University 3
Boston University 3
Universite de Bretagne Occidentale 3
Hewlett-Packard Inc. 3
Tunghai University 3
University of New Orleans 3
Portland State University 3
University of Brasilia 3
Stony Brook University 3
University of Melbourne 3
University of Pisa 3
Cisco Systems 3
Budapest University of Technology and Economics 3
University of Oklahoma 3
Northeastern University China 3
University of Texas System 3
Hunan University 3
University of Seville 3
University of Cyprus 3
Laboratoire Traitement et Communication de l'Information 3
Sunchon National University 4
National Technical University of Athens 4
TIMA Laboratoire 4
University of Peloponnese 4
Northwestern Polytechnical University China 4
University College Dublin 4
Motorola Austin 4
Louisiana State University 4
Chung Hua University 4
City University of Hong Kong 4
Peking University 4
Nanhua University Taiwan 4
Canakkale 18th March University 4
Politecnico di Milano 4
Motorola 4
Hanyang University 4
University of Cincinnati 4
Swiss Federal Institute of Technology, Zurich 4
Microsoft Corporation 4
IBM Austin Research Laboratory 4
University of Milan 4
Syracuse University 4
Universite de Rennes 1 4
Pohang University of Science and Technology 4
University of Dortmund 4
Macronix International Co 4
Laboratoire des Sciences et Techniques de l'Information, de la Communication et de la Connaissance 4
Western Michigan University 5
Royal Institute of Technology 5
University of Calgary 5
Zhejiang University 5
Instituto Superior Tecnico 5
Rice University 5
Universitat Politecnica de Catalunya 5
Technical University of Darmstadt 5
Norwegian University of Science and Technology 5
Texas Instruments 5
University of Tennessee Space Institute 5
Philips Research 5
RWTH Aachen University 5
National University of Singapore 5
University of Bristol 5
New York University 5
University of North Texas 5
Agilent Technologies 5
University of New South Wales 5
Technical University of Madrid 5
IBM Zurich Research Laboratory 5
Kyushu Institute of Technology 5
Nanjing University 5
Fujitsu America, Inc. 5
New York University Abu Dhabi 5
Instituto de Engenharia de Sistemas e Computadores Investigacao e Desenvolvimento em Lisboa 6
North Carolina State University 6
University of Illinois 6
Hong Kong University of Science and Technology 6
Fudan University 6
Indian Institute of Technology, Guwahati 6
Brown University 6
University of California, Davis 6
Holst Centre 6
Industrial Technology Research Institute of Taiwan 6
STMicroelectronics 6
Swiss Federal Institute of Technology, Lausanne 6
Northeastern University 6
University of Verona 6
Universite Nice Sophia Antipolis 6
Magma Design Automation, Inc. 6
Nebrija University 6
Universidade de Lisboa 6
University of Minnesota System 7
Linkoping University 7
HP Labs 7
IBM Thomas J. Watson Research Center 7
National Chung Hsing University 7
Polytechnic School of Montreal 7
Massachusetts Institute of Technology 7
Technion - Israel Institute of Technology 7
Shanghai Jiaotong University 7
National Taiwan University of Science and Technology 7
State University of Campinas 7
Utah State University 7
Iowa State University 8
University of Electronic Science and Technology of China 8
Nanyang Technological University 8
Northwestern University 8
Federal University of Santa Catarina 8
Technical University of Munich 8
University of California, Santa Cruz 8
University of Bologna 8
University of Wisconsin Madison 8
Indian Institute of Technology, Delhi 8
Karlsruhe Institute of Technology 8
Ulsan National Institute of Science and Technology 8
University of Michigan 9
McGill University 9
University of Auckland 9
University of Bonn 9
University of Texas at Dallas 9
University of Montreal 9
Stanford University 9
Drexel University 9
Fuzhou University 9
Freescale Semiconductor 9
University of Connecticut 9
National Central University Taiwan 9
University of Freiburg 9
University of Illinois at Chicago 9
The University of British Columbia 10
University of Stuttgart 10
NEC Laboratories America, Inc. 10
University of Iowa 10
Indian Statistical Institute, Kolkata 10
University of Utah 10
Broadcom Corporation 10
Sharif University of Technology 10
University of Minnesota Twin Cities 10
Southern Illinois University at Carbondale 10
Chung Yuan Christian University 10
NEC Corporation 10
Princeton University 11
Yuan Ze University 11
University of Massachusetts Amherst 11
Imperial College London 11
University of Notre Dame 11
Indian Institute of Technology, Madras 11
Samsung Electronics Co. Ltd. 12
Federal University of Rio Grande do Sul 12
University of Florida 12
University of Waterloo 12
Korea Advanced Institute of Science & Technology 12
Universite Grenoble Alpes 12
National University of Defense Technology China 13
University of Patras 13
University of South Florida Tampa 14
Academia Sinica Taiwan 14
University of Science and Technology of China 14
Catholic University of Leuven, Leuven 14
Complutense University of Madrid 14
National Chung Cheng University 15
Hong Kong Polytechnic University 15
University of Tehran 15
University of California, Berkeley 15
Renesas Electronics Corporation 15
Chinese Academy of Sciences 16
University of Arizona 17
University of Erlangen-Nuremberg 18
Cadence Design Systems 18
University of Southern California 18
Ghent University 18
Pennsylvania State University 20
Arizona State University 20
Georgia Institute of Technology 20
Virginia Tech 20
University of Illinois at Urbana-Champaign 21
University of California, Santa Barbara 21
Tsinghua University 24
National Cheng Kung University 25
University of Maryland 26
Eindhoven University of Technology 27
Synopsys Incorporated 28
Chinese University of Hong Kong 30
Duke University 31
University Michigan Ann Arbor 32
Intel Corporation 33
Polytechnic Institute of Turin 34
Interuniversity Micro-Electronics Center at Leuven 34
University of Texas at Austin 35
University of Pittsburgh 37
Carnegie Mellon University 40
Purdue University 41
National Taiwan University 42
University of California, San Diego 43
National Chiao Tung University Taiwan 44
University of California, Riverside 44
Texas A and M University 51
Indian Institute of Technology, Kharagpur 55
University of California, Irvine 63
University of California, Los Angeles 65
National Tsing Hua University 70
Seoul National University 71

ACM Transactions on Design Automation of Electronic Systems (TODAES)

Volume 22 Issue 2, February 2017  Issue-in-Progress

Volume 22 Issue 1, December 2016
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Volume 21 Issue 3, July 2016 Special Section on New Physical Design Techniques for the Next Generation Integration Technology and Regular Papers
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Volume 16 Issue 4, October 2011
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Volume 16 Issue 1, November 2010
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Volume 3 Issue 4, Oct. 1998
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