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An Accuracy Tunable Non-Boolean Co-Processor Using Coupled Nano-Oscillators

As we enter an era witnessing the closer end of Dennard scaling, where further reduction in power supply-voltage to reduce power consumption becomes... (more)

Design Considerations for Memristive Crossbar Physical Unclonable Functions

Hardware security has emerged as a field concerned with issues such as integrated circuit (IC)... (more)

Statistical Optimization of FinFET Processor Architectures under PVT Variations Using Dual Device-Type Assignment

With semiconductor technology scaling to the 22nm node and beyond, fin field-effect transistor... (more)

Heterogeneous HMC+DDRx Memory Management for Performance-Temperature Tradeoffs

Three-dimensional DRAMs (3D-DRAMs) are emerging as a promising solution to address the memory wall problem in computer systems. However, high... (more)

Robust In-Field Testing of Digital Microfluidic Biochips

Microfluidic technology offers vast promise for implementing biochemistry-on-chip with diverse applications to clinical diagnosis, genome analysis,... (more)

Resource-Constrained Scheduling for Digital Microfluidic Biochips

Digital microfluidics based on electrowetting-on-dielectric technology is poised to revolutionize many aspects of chemistry and biochemistry through... (more)

Impact of Process Variation on Self-Reference Sensing Scheme and Adaptive Current Modulation for Robust STTRAM Sensing

Spin-Transfer-Torque RAM (STTRAM) is a promising technology for high-density on-chip cache due to... (more)

Improving Energy Efficiency in Wireless Network-on-Chip Architectures

Wireless Network-on-Chip (WiNoC) represents a promising emerging communication technology for addressing the scalability limitations of future... (more)

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About JETC

The Journal of Emerging Technologies in Computing Systems invites submissions of original technical papers describing research and development in emerging technologies in computing systems. Major economic and technical challenges are expected to impede the continued scaling of semiconductor devices. This has resulted in the search for alternate mechanical, biological/biochemical, nanoscale electronic, asynchronous and quantum computing and sensor technologies. 

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A GPU-Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks

FPGA-based hardware accelerators for convolutional neural networks (CNNs) have obtained great attentions due to their higher energy efficiency than GPUs. However, it is challenging for FPGA-based solutions to achieve a higher throughput than GPU counterparts. In this paper, we demonstrate that FPGA acceleration can be a superior solution in terms of both throughput and energy efficiency when a CNN is trained with binary constraints on weights and activations. Specifically, we propose an optimized FPGA accelerator architecture tailored for bitwise convolution and normalization that features massive spatial parallelism with deep pipelines stages. A key advantage of the FPGA accelerator is that its performance is insensitive to data batch size, while the performance of GPU acceleration varies largely depending on the batch size of the data. Experiment results show that the proposed accelerator architecture for binary CNNs running on a Virtex-7 FPGA is 8.3x faster and 75x more energy-efficient than a Titan X GPU for processing online individual requests in small batch sizes. For processing static data in large batch sizes, the proposed solution is on a par with a Titan X GPU in terms of throughput while delivering 9.5x higher energy efficiency.

Guest Editors' Introduction: Frontiers of Hardware and Algorithms for On-chip Learning

A Learning-Based Thermal-Sensitive Power Optimization Approach for Optical NoCs

Optical networks-on-chip (NoCs) based on silicon photonics have been proposed as emerging on-chip communication architectures for chip multiprocessors with large core counts. However, due to thermal sensitivity of optical devices used in optical NoCs, on-chip temperature variations cause significant thermal-induced optical power loss which would counteract the power advantages of optical NoCs. To tackle this problem, in this work, we propose a learning-based thermal-sensitive power optimization approach for mesh or torus-based optical NoCs in presence of temperature variations. The key techniques proposed includes an initial device setting and thermal tuning mechanism which is a device-level optimization technique, and a learning-based thermal-sensitive adaptive routing algorithm which is a network-level optimization technique. Simulation results of an 8x8 mesh-based optical NoC show that the proposed initial device setting and thermal tuning mechanism confines the worst-case thermal-induced energy consumption to be on the order of tens of pJ/bit, by avoiding significant thermal-induced optical power loss caused by temperature-dependent wavelength shifts. Besides, it shows that the learning-based thermal-sensitive adaptive routing algorithm is able to find an optimal path with the minimum estimated thermal-induced power consumption for each communication pair. The proposed routing has a greater space for optimization especially for applications with more long-distance traffic.

An Integrated Nanophotonic Parallel Adder

ntegrated optical circuits with nanophotonic devices have attracted significant attention due to its low power dissipation and light-speed operation. With light interference and resonance phenomena, the nanophotonic device works as a voltage-controlled optical pass-gate like a pass-transistor. This paper first introduces a concept of the optical pass-gate logic, and then proposes a parallel adder circuit based on the optical pass-gate logic. Experimental results obtained with an optoelectronic circuit simulator show advantages of our optical parallel adder circuit over a traditional CMOS-based parallel adder circuit.

A Chip-level Anti-reverse Engineering Technique

Protection of intellectual property (IP) is increasingly critical for IP vendors in semiconductor industry. However, advanced reverse engineering techniques can physically disassemble the chip and derive the IPs at a much lower cost than the value of IP design that chips carry. This invasive hardware attack obtaining information from IC chips always violates the IP rights of vendors. The intent of this paper is to present a chip- level reverse engineering resilient design technique. In the proposed technique, transformable interconnects enable an IC chip to maintain functioning in normal use and to transform its physical structure into another pattern when exposed to invasive attacks. The newly-created patten will signi cantly increase the di culty of reverse engineering. Furthermore, to improve the e ectiveness of the proposed technique, a systematic design method is developed targeting integrated circuits with multiple design constraints. Simulations have been conducted to demonstrate the capability of the proposed technique, which generates extremely large complexity for reverse engineering with manageable overhead.

Framework for Quantifying and Managing Accuracy in Stochastic Circuit Design

Stochastic circuits (SCs) offer tremendous area- and power-consumption benefits at the expense of computational inaccuracies. Unlike conventional logic synthesis, managing accuracy is a central problem in SC design. It is usually tackled in ad hoc fashion by multiple trial-and-error simulations that vary relevant parameters like the stochastic number length n. We present, for the first time, a systematic design approach to controlling the accuracy of SCs and balancing it against other design parameters. We express the (in)accuracy of a circuit processing n-bit stochastic numbers by the numerical deviation of the computed value from the expected result, in conjunction with a confidence level. Using the theory of Monte Carlo simulation, we derive expressions for the stochastic number length required for a desired level of accuracy, or vice versa. We discuss the integration of the theory into a design framework that is applicable to both combinational and sequential SCs. We show that for combinational SCs, accuracy is independent of the circuit's size or complexity, a surprising result. We also show how the analysis can identify subtle errors in both combinational and sequential designs. Finally, we apply the proposed methods to a case study on filtering noisy EKG signals.

Kogge-Stone Adder Realization using 1S1R Resistive Switching Crossbar Arrays

Low operating voltage, high storage density, non-volatile storage capabilities and relative low access latencies have popularized memristive devices as storage devices. Memristors can be ideally used for in-memory computing in the form of hybrid CMOS nano-crossbar arrays. In-memory serial adders have been theoretically and experimentally proven for crossbar arrays. To harness the parallelism of memristive arrays, parallel-prefix adders can be effective. In this work, a novel mapping scheme for in-memory Kogge-Stone adder has been presented. The number of cycles increases logarithmically with the bit width N of the operands i.e. O(log2N) and the device count is 5N. We verify the correctness of the proposed scheme by means of TaOx device model based memristive simulations. We compare the proposed scheme with other proposed schemes in terms of number of cycle and number of devices.

Editorial: Silicon Photonics for Computing Systems

Real-Time and Low-Power Streaming Source Separation Using Markov Random Field

As a step towards solving the problem of implementing a usable machine learning application, especially perceptual tasks, on a mobile form factor, we explore sound source separation to isolate human voice from background noise on a mobile phone. The challenges involved are real-time streaming execution and power constraints. As a solution, we present a novel hardware-base sound source separation capable of real-time streaming performance while consuming low power. The implementation uses Markov Random Field (MRF) formulation of Blind Source Separation (BSS) with two microphones. It uses Expectation-Maximization (EM) to learn hidden MRF parameters on the fly and also performs Maximum A Posterior (MAP) inference using Gibbs sampling to find the best separation of sources. We demonstrate a real-time streaming FPGA implementation running at 150 MHz with 207 KB RAM. It achieves a speed-up of 22X over a conventional software reference, performs with an SDR of up to 7.021 dB with 1.601 ms latency, and exhibits excellent perceived audio quality. A virtual ASIC design study shows that this architecture is small with less than 10M gates, consumes only 40.034 mW (which is only 10% of power on ARM Cortex-A9) running at 150 MHz.

Design Space Exploration of 3D Network-on-Chip: A Sensitivity-based Optimization Approach

High-performance and energy-efficient Network-on-Chip (NoC) architecture is one of the crucial components of the manycore processing platforms. A very promising NoC architecture recently proposed in the literature is the three-dimensional small-world NoC (3D SWNoC). Due to short vertical links in 3D integration and the robustness of small-world networks, the 3D SWNoC architecture outperforms its other 3D counterparts. However, the performance of 3D SWNoC is highly dependent on the placement of the links and associated routers. In this paper, we propose a sensitivity-based link placement algorithm (SEN) to optimize the performance of 3D SWNoC.We compare the performance of SEN algorithm with simulated annealing- (SA) and recently proposed machine learning-based (ML) optimization algorithm. The optimized 3D SWNoC obtained by the proposed SEN algorithm achieves, on average, 11.5% and 13.6% lower latency and 18.4% and 21.7% lower energy-delay product than those optimized by the SA and ML algorithms respectively. In addition, the SEN algorithm is 26 to 33 times faster than the SA algorithm for the optimization of 64-, 128-, and 256-core 3D SWNoC designs.However, we find that ML-based methodology has faster convergence time than SEN and SA for bigger systems.

Integrated High Speed Optical SerDes over 100GBd Based on Optical Time Division Multiplexing

An on-chip optical transceiver for 100GBd+ transmission system is proposed based on optical time division multiplexing (OTDM) technology. Co-designed with the double rail driver, on-chip Mach-Zehnder interferometer (MZI) switch repeatedly generates extremely narrow sampling pulses of only 12ps full width at half maximum (FWHM). The 4-stage cascaded high speed switches driven synchronously at 25GHz are employed to divide the 40ps clock cycle into 4 recurrent 9.5ps time slots, each for one sub-channel, and one time slot of 2ps for clock recovery. Thus, a 100GBd optical transmission channel is realized based on 4 bit 25Gbps bit-streams at the electrical interface. The crosstalk extinction ratio at the worst sub-channel is 1.9dB with 10dB depth modulator, and the insertion loss caused by the OTDM mechanism is about 10dB. Further, a 5-bit OTDM system based on dark modulation is proposed to generate a 125GBd transmission based on 5 bit 25Gbps bit-streams at the electrical interface. The extinction ratio performance is better even the symbol rate is higher. However, the insertion loss and electron complexity are sacrificed.

A Process Variation Tolerant Method for Nanophotonic On-chip Network

Nanophotonic networks have been challenged for their reliability due to several device-level limitations. One of the main issues is that fabrication errors can cause devices to malfunction, rendering communication unreliable. For example, microring resonator, a preferred optical modulator device, may not resonate at the designated wavelength under process variations (PV), leading to communication errors and bandwidth loss. This paper proposes a series of solutions to the wavelength drifting problem of microrings due to PV. The objective is to maximize network bandwidth through proper arrangement among microrings and wavelengths with minimum power requirement. Our arrangement, called ``MinTrim", solves this problem using simple integer linear programming, adding supplementary microrings and allowing flexible assignment of wavelengths to network nodes as long as the resulting network presents maximal bandwidth. Each step is shown to improve bandwidth provisioning with lower power requirement. Evaluations on a sample network show that a baseline network could lose more than 40% bandwidth due to PV. Such loss can be recovered by MinTrim to produce a network with 98.4% working bandwidth. In addition, the power required in arranging microrings is 39% lower than the baseline. Therefore, MinTrim provides an efficient PV-tolerant solution to improving the reliability of on-chip photonics.

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

Current Deep Learning approaches that have been very successful use convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers. Three limitations of this approach are: 1) they are based on a simple layered network topology, i.e., highly connected layers, without intra-layer connections; 2) the networks are manually configured to achieve optimal results, and 3) the implementation of neuron model is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determine network topology, and neuromorphic computing for a low-power hardware implementation. We use the MNIST dataset for our experiment, due to input size limitations of current quantum computers. Our results show the feasibility of using the three architectures in tandem to address the above deep learning limitations. We show a quantum computer can find high quality values of intra-layer connections weights, in a tractable time as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware.

MFNW: An MLC/TLC Flip-N-Write Architecture

The increased capacity of multi-level cells (MLC) and triple-level cells (TLC) in emerging non-volatile memory (NVM) technologies comes at the cost of higher cell write energies and lower cell endurance. In this paper, we describe MFNW, a Flip-N-Write encoding that effectively reduces the write energy and improves the endurance of MLC NVMs. Two MFNW modes are analyzed: cell Hamming distance (CHD) mode and energy Hamming distance (EHD) mode. We derive an ap- proximate model that accurately predicts the average number of cell writes that is proportional to the energy consumption, enabling word length optimization to maximize energy reduction subject to memory overhead constraints. In comparison to state-of-the-art MLC NVM encodings, our simulation results indicate that MFNW achieves up to 7%39% saving for 1.56%50% NVM overhead. Extra energy saving (up to 19%47%) can be achieved for the same NVM overhead using our proposed variations of MFNW, i.e., MFNW2 and MFNW3. For TLC NVMs, we propose TFNW that can achieve up to 53% energy saving in comparison to state-of-the-art TLC NVM encodings. Endurance simulations indicate that MFNW (TFNW) is capable of extending MLC (TLC) NVM life by up to 100% (87%).

Reducing power consumption of lasers in photonic NoCs through application-specific mapping

To face the complex communication problems that arise as the number of on-chip components grows up, photonic networks-on-chip have been recently proposed to replace electronic interconnects. However, photonic networks-on-chip lack efficient laser sources, possibly resulting in an inefficient or inoperable architecture. In this technical note, we introduce a methodology for the design space exploration of optical NoC mapping solutions, which automatically assigns application tasks to the network tiles such that the total laser power consumption is minimized. The experimental evaluation shows average reductions of 34.7% and 27.35% in the power consumption compared to respectively application-oblivious and randomly mapped photonic NoCs, allowing improved energy efficiency.

Offline optimization of wavelength allocation and laser power in nanophotonic interconnects

ONoC is a promising communication medium for large-scale MPSoC. Indeed ONoC can outperform classical electrical NoC in terms of energy efficiency and bandwidth density, in particular, because this medium can support multiple transactions at the same time on different wavelengths by using WDM. However, multiple signals sharing simultaneously the same part of a waveguide can lead to inter-channel crosstalk noise. is problem impacts the Signal to Noise Ratio (SNR) of the optical signals, which leads to an increase in the Bit Error Rate at the receiver side. If a specific BER is targeted, an increase of laser power should be necessary to satisfy the SNR. In this context, an important issue is to evaluate the laser power needed to satisfy the various desired communication bandwidths based on the BER performance requirements. In this paper, we propose an o -line approach that concurrently optimizes the laser power scaling and execution time of a global application. A set of different levels of power is introduced for each laser, to ensure that optical signal can be emitted with just-enough power to ensure targeted BER. As result, most promising solutions are highlighted for mapping a defined application onto 16-core ring-based WDM ONoC.

SHARP: Shared Heterogeneous Architecture with Reconfigurable Photonic Network-on-Chip

As the relentless quest for higher throughput and lower energy cost continues in heterogenous multicores, there is a strong demand for energy-efficient and high-performance Network-on-Chip (NoC) architectures. Photonic interconnects are a disruptive technology solution that has the potential to increase the bandwidth, reduce latency, and improve energy-efficiency over traditional metallic interconnects. In this paper, we propose a CPU-GPU heterogeneous architecture called SHARP (Shared Heterogeneous Architecture with Reconfigurable Photonic Network-on-Chip) that clusters CPU and GPU cores around the same router and dynamically allocates bandwidth between the CPU and GPU cores based on application demands. The SHARP architecture is designed as a Single-Writer Multiple-Reader (SWMR) crossbar with reservation-assist to connect CPU/GPU cores that dynamically reallocates bandwidth using buffer utilization information at runtime. As network traffic exhibits temporal and spatial fluctuations due to application behavior, SHARP can dynamically reallocate bandwidth and thereby adapt to application demands. SHARP demonstrates 34% performance (throughput) improvement over a baseline electrical CMESH while consuming 25% less energy per bit. Simulation results have also shown 6.9% to 14.9% performance improvement over other flavors of the proposed SHARP architecture without dynamic bandwidth allocation.

Bibliometrics

Publication Years 2005-2018
Publication Count 371
Citation Count 968
Available for Download 371
Downloads (6 weeks) 2304
Downloads (12 Months) 18580
Downloads (cumulative) 158539
Average downloads per article 427
Average citations per article 3
First Name Last Name Award
Iris Bahar ACM Distinguished Member (2012)
Krishnendu Chakrabarty ACM Fellows (2013)
ACM Distinguished Member (2008)
ACM Senior Member (2006)
Jason Cong ACM Fellows (2008)
Giovanni DeMicheli ACM Fellows (2001)
Nikil D. Dutt ACM Fellows (2014)
ACM Distinguished Member (2007)
John P Hayes ACM Fellows (2001)
Niraj Jha ACM Fellows (2003)
Andrew Kahng ACM Fellows (2012)
Gabriel H Loh ACM Fellows (2017)
ACM Distinguished Member (2014)
ACM Senior Member (2009)
Roman Lysecky ACM Senior Member (2014)
Sharad Malik ACM Fellows (2014)
Igor Markov ACM Distinguished Member (2011)
ACM Senior Member (2007)
Margaret Martonosi ACM Fellows (2009)
Subhasish Mitra ACM Fellows (2014)
Dharmendra Modha ACM Gordon Bell Prize
Special Category (2009) ACM Gordon Bell Prize
Special Category (2009)
Saraju P. Mohanty ACM Senior Member (2010)
Trevor Mudge ACM Fellows (2016)
ACM-IEEE CS Eckert-Mauchly Award (2014)
Massoud Pedram ACM Distinguished Member (2008)
Dhiraj Pradhan ACM Fellows (1999)
Steven K Reinhardt ACM Distinguished Member (2010)
Sachin S. Sapatnekar ACM Fellows (2016)
John E Savage ACM Fellows (1996)

First Name Last Name Paper Counts
Niraj Jha 21
Krishnendu Chakrabarty 11
Kaushik Roy 8
Wei Zhang 7
Michael Niemier 6
Rodney Van Meter 6
Yuan Xie 6
Li Shang 6
Fabrizio Lombardi 6
Xiaobosharon Hu 5
Pierre Gaillardon 5
Partha Pande 5
Mehdi Tahoori 5
Morteza Zamani 4
Jiang Xu 4
Mariagrazia Graziano 4
Shuo Wang 4
Bhargab Bhattacharya 4
Mehdi Sedighi 4
Lei Wang 4
Alvin Lebeck 4
Mohammad Tehranipoor 4
Chris Dwyer 4
Swaroop Ghosh 3
Mahboobeh Houshmand 3
Mahdi Nikdast 3
Spyros Tragoudas 3
Michael Crocker 3
Paul Wettin 3
Jordi Cortadella 3
Amlan Chakrabarti 3
Vijaykrishnan Narayanan 3
Sourindra Chaudhuri 3
Jianwei Dai 3
Aoxiang Tang 3
Yaoyao Ye 3
Xuan Wang 3
Tao Xu 3
Ferdinand Peper 3
Fei Su 3
Arun Ravindran 3
Jacques Klein 3
Weisheng Zhao 3
Nagarajan Ranganathan 3
Maurizio Zamboni 3
Keshab Parhi 3
Eren Kursun 3
Arindam Mukherjee 3
Robert Wille 3
Tinoosh Mohsenin 3
Xiaowen Wu 3
Kishor Trivedi 3
Rolf Drechsler 3
Vijay Reddy 2
Sumeet Gupta 2
Mostafizur Rahman 2
Csaba Moritz 2
Himanshu Thapliyal 2
Frederic Chong 2
Siddhartha Datta 2
Mehdi Saeedi 2
Chiachun Lin 2
Djaafar Chabi 2
Mrigank Sharad 2
Reza Rad 2
Sachin Sapatnekar 2
Giovanni De Micheli 2
Santosh Khasanvis 2
Harika Manem 2
Jungsang Kim 2
Douglas Densmore 2
Chris Myers 2
Sudip Roy 2
Kolin Paul 2
Stefano Frache 2
Yaojun Zhang 2
Giorgio Natale 2
Lionel Torres 2
Cheng Zhuo 2
Prateek Mishra 2
Bryant Wysocki 2
Bao Liu 2
Garrett Rose 2
Philip Brisk 2
Paolo Grani 2
Massoud Pedram 2
Jacob Murray 2
Giovanni Micheli 2
Saibal Mukhopadhyay 2
John Savage 2
Byungsoo Choi 2
Damien Querlioz 2
Rivalino Matias 2
Xuanyao Fong 2
Oliver Keszocze 2
Sparsh Mittal 2
Suman Datta 2
Lei Wang 2
Ashok Palaniswamy 2
Jing Huang 2
André DeHon 2
Zhehui Wang 2
Tsungyi Ho 2
Mehrdad Nourani 2
Min Chen 2
Sungkyu Lim 2
Alexis De Vos 2
Veezhinathan Kamakoti 2
Faquir Jain 2
Muhammad Ahsan 2
Anil Wipat 2
Pallav Gupta 2
Shashikanth Bobba 2
Josep Carmona 2
Marco Ottavi 2
Bharat Joshi 2
Philippe Coussy 2
Ruth Bahar 2
Xianmin Chen 2
Mona Arabzadeh 2
Giovanni De Micheli 2
Jaidev Patwardhan 2
Luca Schiano 2
Yongtae Kim 2
Bipul Paul 2
Baris Taskin 2
Arighna Deb 2
Ulf Schlichtmann 2
Amlan Ganguly 2
Eric Rachlin 2
John Hayes 2
Peng Li 2
Dhiraj Pradhan 2
Deliang Fan 2
Torben Mogensen 2
Hafizur Rahaman 2
Swarup Bhunia 2
Xueqing Li 2
Debasis Mitra 2
Daniel Grissom 2
Sandro Bartolini 2
Behrooz Shirazi 2
Rangharajan Venkatesan 2
Anand Raghunathan 2
Dang Nguyen 1
Zhenyu Sun 1
Amip Shah 1
Radu Marculescu 1
Sajal Das 1
Keren Bergman 1
Michal Lipson 1
Hongyu Zhou 1
M Najafi 1
Honglan Jiang 1
Anuj Arora 1
Holger Axelsen 1
Greg Snider 1
Trung Nguyen 1
Suyog Gupta 1
Robert Karam 1
Kyuyeon Hwang 1
Colin Shea 1
Arvind Kumar 1
Yavuz Yetim 1
Anusha Gorantla 1
Wei Chan 1
Andrew Kahng 1
Debasri Saha 1
Ying Wang 1
Mary Eshaghian-Wilner 1
Lucian Prodan 1
Mihai Udrescu 1
Jacob White 1
Gordon Wan 1
Steven Reinhardt 1
Cesare Ferri 1
Sherief Reda 1
Qiaoyan Yu 1
Jonathan Salkind 1
Gerardo Pelosi 1
Jean Dutertre 1
Yu Bi 1
Jiannshiun Yuan 1
Ramprasad Ravichandran 1
Olivier Sentieys 1
Mostafa Azghadi 1
Mehmet Ozdas 1
Edith Beigné 1
Sumeet Gupta 1
Yihang Chen 1
Anja Von Beuningen 1
Luca Ramini 1
Kotb Jabeur 1
Virgile Javerliac 1
Stephane Gros 1
Pierre Paoli 1
Chengwen Wu 1
Keqin Li 1
Liang Wen 1
Wei Chen 1
Xiong Pan 1
Luan Duong 1
Zhifei Wang 1
Antônio Beck 1
Luigi Carro 1
Ney Calazans 1
Kiyoung Choi 1
William Fornaciari 1
El Hasaneen 1
Vivek De 1
Peng Li 1
Yukui Pei 1
Nicholas Roehner 1
Goksel Misirli 1
Rudolf Füchslin 1
Herbert Sauro 1
Biplab Sikdar 1
Mark Hagan 1
Jia Lee 1
Behnam Ghavami 1
Nishad Nerurkar 1
Jie Chen 1
Pratik Kabali 1
Weichen Liu 1
Christine Nardini 1
Yao Xu 1
Yang Liu 1
Vasilis Pavlidis 1
Narayanan Komerath 1
Ransford Hyman 1
Fiona Teshome 1
Gabriel Loh 1
Lloyd Harriott 1
Arthur Nieuwoudt 1
Sezer Gören 1
Luke Pierce 1
Manoj Gaur 1
Ozan Ozbag 1
Juha Plosila 1
Hannu Tenhunen 1
Nilanjan Goswami 1
Oluleye Olorode 1
Michele Dini 1
Woomin Hwang 1
Marco Vacca 1
Jeffrey Pepper 1
Ian O'Connor 1
M Amadou 1
Philippe Matherat 1
John Jr 1
Haldun Kufluoglu 1
Pier Martelli 1
Giuseppe Profiti 1
Alvaro Padilla 1
Simone Raoux 1
Andrea Acquaviva 1
Arijit Raychowdhury 1
Sayeef Salahuddin 1
Satish Kumar 1
Xueti Tang 1
Xiao Luo 1
Wen Ko 1
Pedro Irazoqui 1
Steve Majerus 1
Michael Suster 1
Paul Fletter 1
Muhammad Salam 1
Hsinhung Liao 1
Tao Wang 1
Xiang Chen 1
Prithviraj Banerjee 1
Alan Savage 1
Siddharth Garg 1
Diana Marculescu 1
Andrès Márquez 1
Jacob Levy 1
Rekha Govindaraj 1
Sukeshwar Kannan 1
Michael Thomsen 1
Kamalika Datta 1
Pragyan Mohanty 1
Umamaheswara Tida 1
Yiyu Shi 1
Hao Yu 1
Mohammed Alawad 1
Wei Chen 1
Kihyun Park 1
Krishnendu Guha 1
Jing Ye 1
Chunyi Lee 1
Kang Wang 1
Shiva Navab 1
Albert Lin 1
Nathan Binkert 1
Trevor Mudge 1
Glenn Reinman 1
Shigeto Nakayama 1
David Wolpert 1
Paul Ampadu 1
Stephan De Castro 1
Elena Vatajelu 1
Anirudh Iyengar 1
Kaveh Shamsi 1
Xunzhao Yin 1
Jayita Das 1
Azzurra Pulimeno 1
Youguang Zhang 1
Gefei Wang 1
Xun Gao 1
Hoda Khouzani 1
Fabrice Bernard-Granger 1
Gregory Pendina 1
Meghna Mankalale 1
Lei Wang 1
José Abellán 1
Zhiguang Chen 1
A Goud 1
Liang Rong 1
Arthur Lorenzon 1
Victor Yashin 1
Donald Chiarulli 1
Ernesto Sánchez 1
Kartik Mohanram 1
Runlai Wan 1
V Devanathan 1
Houman Homayoun 1
Bohua Li 1
Andre Van Rynbach 1
Haiyao Huang 1
Claudio Moraga 1
Marek Perkowski, 1
Xiaoyu Song 1
Md Rahman 1
Gerhard Dueck 1
Samik Some 1
Yu Cao 1
Olivier Thomas 1
Kenichi Morita 1
H Wong 1
V Kamakoti 1
A Bhattacharya 1
Soumya Eachempati 1
Yuan Xie 1
Yu Wang 1
Howie Huang 1
Tzvetan Metodi 1
Andrew Cross 1
Jeyavijayan Rajendran 1
Ashok Srivastava 1
Michael Henry 1
Clay Mayberry 1
Benjamin Gojman 1
Krishnendu Chakrabarty 1
Venkataraman Mahalingam 1
Xuemei Chen 1
Kerry Bernstein 1
James Tour 1
Garrett Rose 1
Peter Kogge 1
Zahra Sasanian 1
H Ugurdag 1
Meng Zhang 1
Spyros Tragoudas 1
Jaeyoon Kim 1
Niraj Jha 1
Pohsun Wu 1
Misagh Khayambashi 1
Tao Li 1
Vijay Raghunathan 1
Jue Wang 1
Miguel Lastras-Montaño 1
Melika Payvand 1
Kwangting Cheng 1
Matteo Filippi 1
Dongjin Kim 1
Rajit Manohar 1
Fabien Clermidy 1
Yanbin Wang 1
Roberto Pietrantuono 1
Jing Zhao 1
Gautam Kapila 1
Wensi Wang 1
Terence O'Donnell 1
Rohit Shenoy 1
Bipin Rajendran 1
Elisa Ficarra 1
Subho Chatterjee 1
Alexander Driskill-Smith 1
Swaroop Ghosh 1
Chenpang Kung 1
Steven Garverick 1
Yaojoe Yang 1
Diana Franklin 1
Sandeep Gupta 1
Nicolas Sherwood-Droz 1
Kyle Preston 1
Gilbert Hendry 1
Peng Li 1
Yong Shim 1
Eldhose Peter 1
Stéphane Burignat 1
Tetsuo Yokoyama 1
Alireza Shafaei 1
Taemin Kim 1
Zichuan Liu 1
Sajid Anwar 1
Nong Xiao 1
William Hwang 1
Pierre Mudry 1
Gianluca Tempesti 1
André Stauffer 1
Marya Lieberman 1
Jie Deng 1
Ali Saidi 1
Yongxiang Liu 1
Yuchun Ma 1
Eiri Hashimoto 1
Yutaka Sacho 1
Andy Chiu 1
Alessandro Barenghi 1
Shahed Quadir 1
John Chandy 1
PAOLO Prinetto 1
Mario Barbareschi 1
Jaewon Jang 1
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Tiansheng Zhang 1
Yue Zhang 1
Claude Chappert 1
Sungjun Yoon 1
Jack Sampson 1
Abbas Dehghani 1
Kamal Jamshidi 1
Jianyu Chen 1
Sylvain Claireux 1
Guangyan Zhang 1
Xuhao Chen 1
Ajay Joshi 1
Xia Zhang 1
Hassan Mohammadi 1
Matteo Reorda 1
Davide Zoni 1
Andrew Kahng 1
Rajat Chakraborty 1
Wujie Wen 1
Salvatore Monteleone 1
Xiaokun Yang 1
Ming Fan 1
Zhen Zhang 1
Maik Hadorn 1
Wei Zhang 1
Shengqi Yang 1
Wenping Wang 1
Perrine Batude 1
Michael Leuchtenburg 1
Pinaki Mazumder 1
Pavan Panchapakeshan 1
Csaba Moritz 1
Jan Madsen 1
Christof Teuscher 1
Ali Afzali-Kusha 1
Jie Zhang 1
Isaac Chuang 1
Kohei Itoh 1
Minlun Chuang 1
Ashwani Sharma 1
Aravinda Kar 1
Mark Oskin 1
Jin He 1
Kevin Chang 1
Xinmin Yu 1
M Balakrishnan 1
Sandip Tiwari 1
Weichen Liu 1
Vineet Sahula 1
Shankar Balachandran 1
Yang Du 1
Bertrand Granado 1
Nasim Farahini 1
Ahmed Hemani 1
Ashkan Eghbal 1
AmirAli Ghofrani 1
Luke Theogarajan 1
Chulmin Kim 1
Kyuho Park 1
Hyunchul Seok 1
Jun Pang 1
Alex Yakovlev 1
Steve Furber 1
Simon Davidson 1
Steve Temple 1
Nor Haron 1
Said Hamdioui 1
Roberto Natella 1
Roman Lysecky 1
Janet Roveda 1
Chung Lam 1
Gregory Corrado 1
Roger Cheek 1
Charles Rettner 1
Wengfai Wong 1
Chengkok Koh 1
R Williams 1
Dmytro Apalkov 1
Penli Huang 1
Hai Li 1
Yiran Chen 1
Vlasia Anagnostopoulou 1
Georgios Varsamopoulos 1
Hengxing Tan 1
Moustafa Mohamed 1
Chamika Liyanagedera 1
Abhishek Koneru 1
Karthik Yogendra 1
Jie Han 1
Cong Liu 1
Stijn De Baerdemacker 1
Ruchir Puri 1
Leibin Ni 1
Margaret Martonosi 1
Jiajia Li 1
Thomas Lee 1
Shinobu Fujita 1
Krisztiàn Flautner 1
Yifang Liu 1
Yang Yi 1
Franjo Ivančić 1
Martin Roetteler 1
Yu Liu 1
Mohammad Tavana 1
MD Majumder 1
Neel Gala 1
Sarada Krithivasan 1
Seyedhamidreza Motaman 1
Erik Lindgren 1
Jennifer Hallinan 1
Harold Fellermann 1
Zhiqiang Li 1
Bibhash Sen 1
Anuroop Vidapalapati 1
Guangyu Sun 1
Masoud Zamani 1
S Srinivasan 1
Mohsen Raji 1
Hossein Pedram 1
Huazhong Yang 1
Tingting Hwang 1
Matthias Beste 1
Darshan Thaker 1
Kouichi Akahane 1
Daniel Sorin 1
Minhao Zhu 1
Suman Sah 1
Benjamin Belzer 1
Vivek Shende 1
Jonathan Bean 1
Weiguo Tang 1
Okan Palaz 1
Shunming Syu 1
Rodney Meter 1
Syyen Kuo 1
Marc Galceran-Oms 1
John Bainbridge 1
Aaron Dingler 1
Stefano Russo 1
Senthil Arasu 1
Fumio Machida 1
Jean Araujo 1
Paulo Maciel 1
Mike Hayes 1
Justin Wenck 1
Takanori Maebashi 1
Dennis Huo 1
Luca Breveglieri 1
Qianying Tang 1
Youngok Pino 1
Matthew French 1
Trongnhan Le 1
Arnaud Carer 1
Wang Kang 1
Qian Wang 1
Juinndar Huang 1
Yuan Xue 1
Chengmo Yang 1
Guillaume Prenat 1
Debesh Das 1
Anand Raghunathan 1
Arnab Biswas 1
Zhe Wang 1
Yao Wang 1
Peter Beerel 1
Matheus Moreira 1
Jinho Lee 1
Kyungsu Kang 1
Naser MohammadZadeh 1
Weikai Shih 1
Nathan McDonald 1
Muzaffer Simsir 1
Weiyu Tsai 1
Mesbah Uddin 1
Andrea Mineo 1
Davide Patti 1
Ye Yu 1
Jaydeep Kulkarni 1
Natalio Krasnogor 1
Jude Rivers 1
Amlan Gangul 1
Pritish Narayanan 1
Saeed Safari 1
Manoj Yuvaraj 1
Fuwei Chen 1
Vineeth Vijayakumaran 1
Makoto Naruse 1
Naokatsu Yamamoto 1
Motoichi Ohtsu 1
William Munro 1
Chunyao Wang 1
Hu Xu 1
Bryan Black 1
Rajeevan Amirtharajah 1
Kathleen Marchal 1
Jos Vanderleyden 1
Damiano Piovesan 1
Enrico Macii 1
Wujie Wen 1
Vladimir Nikitin 1
Daniel Lottis 1
Kiseok Moon 1
Kwangting Cheng 1
Margot Damaser 1
Martin Arlitt 1
Tao Yang 1
David Du 1
Tridib Mukherjee 1
Hafiz Sheikh 1
Ishfaq Ahmad 1
Landon Sego 1
Manish Vachharajani 1
Mark Cianchetti 1
David Albonesi 1
Hui Li 1
Martha Sepúlveda 1
Smruti Sarangi 1
Mrityunjay Ghosh 1
Yu Cao 1
Dhireesha Kudithipudi 1
Pareesa Golnari 1
Mingjie Lin 1
Armin Alaghi 1
Songping Yu 1
Fang Liu 1
Yu Hu 1
Xiaowei Li 1
Daniel Mange 1
Chialin Yang 1
Oana Boncalo 1
H Wong 1
Yong Zhan 1
Taeho Kgil 1
Natsuo Nakamura 1
Dan Venutolo 1
Marie Flottes 1
Junlin Chen 1
Mark Tehranipoor 1
Yier Jin 1
Amey Kulkarni 1
Douglas Tougaw 1
Yang Zhao 1
Mircea Stan 1
Timothy Dysart 1
Michael Gladshtein 1
Jeffrey Krichmar 1
Yong Zhang 1
Benoît Miramond 1
Hugues Wouafo 1
Syed Jafri 1
Siddharth Gaba 1
Seongmin Kim 1
Michael Kishinevsky 1
Basit Sheikh 1
Delong Shang 1
Cathy Chancellor 1
Claude Cirba 1
Ahmed Louri 1
Rubens Matos 1
F De Souza 1
Ningning Wang 1
Brendan O'Flynn 1
Cian O'Mathuna 1
Jeff Siebert 1
Jianjia Chen 1
Lothar Thiele 1
Piero Fariselli 1
Matthew Breitwisch 1
Kailash Gopalakrishnan 1
Niladri Mojumder 1
Adrian Ong 1
Eugene Chen 1
Jing Li 1
Muthukumar Murugan 1
Zahra Abbasi 1
Phanisekhar Bv 1
Sanjay Ranka 1
Kevin Fox 1
Christopher Mundy 1
Johnnie Chan 1
Zheng Li 1
Kia Bazargan 1
Leibo Liu 1
Janibul Bashir 1
Guoqing Chen 1
Robert Glück 1
Indranil Sengupta 1
Sanjukta Bhanja 1
Ayse Coskun 1
Ruiyu Wang 1
Massimo Roch 1
Roger Lake 1
Zhaohao Wang 1
William Cane-Wissing 1
Loic Decloedt 1
Hang Zhang 1
Angsuman Sarkar 1
Keran Zhou 1
Gilles Sassatelli 1
Houle Gan 1
Tanay Karnik 1
Milad Maleki 1
Srihari Cadambi 1
Kenneth O'Neal 1
Curtis Madsen 1
Ashutosh Chakraborty 1
Xuehui Zhang 1
Prachi Joshi 1
Yungchih Chen 1
Haera Chung 1
Christopher Curtis 1
Yuchun Ma 1
Simeranjit Brar 1
Kae Nemoto 1
Steven Rubin 1
Gilda Garretón 1
Sujay Deb 1
Deukhyoun Heo 1
Ketan Patel 1
Wei Zhao 1
Nabanita Majumdar 1
Nadine Gergel-Hackett 1
Yuxing Yao 1
Gabriel Schulhof 1
Dong Xiang 1
Jifeng Chen 1
Renu Kumawat 1
Bernard Girau 1
Laurent Rodriguez 1
Jiunli Lin 1
Zhongqi Li 1
Hrishikesh Jayakumar 1
Woosuk Lee 1
Aldo Romani 1
Chinghwa Cheng 1
Xin Li 1
Cory Merkel 1
Manan Suri 1
Abhronil Sengupta 1
Wonyong Sung 1
Adam Page 1
Ali Jafari 1
Subramanian Iyer 1
Yakir Vizel 1
Mingzhu Deng 1
Youngsun Youn 1
Shindug Kim 1
Bing Li 1
Yin Liu 1
Yaowen Chang 1
Bruce Tidor 1
Jason Cong 1
Shinjiro Toyoda 1
Jie Chen 1
Ruggero Susella 1
Guido Bertoni 1
Stefano Sanfilippo 1
Yingjie Lao 1
Navid Asadizanjani 1
Kenneth Ramclam 1
Stefan Hillmich 1
Kevin Scott 1
Jie Meng 1
Giacomo Indiveri 1
Can Sitik 1
Emre Salman 1
Suzanne Lesecq 1
Lungyen Chen 1
Laurent Becker 1
Kalyan Biswas 1
Ke Jiang 1
Peng Yang 1
Haibo Wang 1
Stephan Wong 1
Brandon Jennings 1
Steven Levitan 1
Ramy Tadros 1
Joydeep Rakshit 1
Tayebeh Bahreini 1
Milan Patnaik 1
Martin Barke 1
Clare Thiem 1
Lu Wang 1
Mohammad Hajkazemi 1
Nahid Hossain 1
Victor Nicola 1
Avinash Kodi 1
Bryan Jackson 1
Hai Li 1
Charles Augustine 1
Huaiyuan Tseng 1
Yujie Huang 1
Yaohong Wang 1
Krishna Kant 1
Giacomo Ghidini 1
Tahir Cader 1
Andrew Rawson 1
William Gustafson 1
Aleksandr Biberman 1
Qianfan Xu 1
Alan Mickelson 1
David Lilja 1
Marc Riedel 1
Kourosh Marjoei 1
Ian O'Connor 1
Sébastien Beux 1
Akriti Bagaria 1
Sandeep Samal 1
Eva Rotenberg 1
Ismo Hänninen 1
Craig Lent 1
Ryangary Kim 1
Rajiv Joshi 1
Zhe Wan 1
Winfried Wilcke 1
Deepa P 1
Sharad Malik 1
Travis Humble 1
Masaki Okajima 1
Andy Tyrrell 1
Andrew Greensted 1
Pinghung Yuh 1
Joël Rossier 1
Alexander Khitun 1
Mircea Vlăduţiu 1
Lukáš Sekanina 1
Nobuaki Miyakawa 1
Z Wang 1
Huaixiu Zheng 1
Chris Kim 1
Bruno Rouzeyre 1
Nathaniel Cady 1
Sukanta Bhattacharjee 1
Vincenzo Catania 1
Maurizio Palesi 1
Swapnil Bhatia 1
Manojit Dutta 1
Woohyung Lee 1
ChiOn Chui 1
Jorge Kina 1
Stanley Yeh 1
Paul Pop 1
Chunyao Wang 1
Wulong Liu 1
Naseef Mansoor 1
Guru Venkataramani 1
Teng Lu 1
Zhehui Wang 1
H Wong 1
Subhasish Mitra 1
James Donald 1
Xiaojun Ma 1
Jeremy Tolbert 1
Tadashi Kawazoe 1
Jiale Huang 1
Mukta Farooq 1
Charles Lieber 1
Igor Markov 1
Yu Cao 1
Adam Cabe 1
Yehia Massoud 1
Konrad Walus 1
Kushal Datta 1
Ajay Bhoj 1
Ingchao Lin 1
Laura Conde-Canencia 1
Arnab Raha 1
Wei Lu 1
Alexander Gotmanov 1
Fei Xia 1
Masud Chowdhury 1
Xuefu Zhang 1
Junchen Liu 1
Gabriela Nicolescu 1
Yuliang Jin 1
Karthik Shankar 1
Taşkın Koçak 1
Saraju Mohanty 1
Lyn Venken 1
Domenic Forte 1
Sina Shahbazmohamadi 1
Marco Indaco 1
K Habib 1
Alain Pegatoquet 1
Olivier Berder 1
Saber Moradi 1
Daniel Fasnacht 1
Leo Filippini 1
D Miller 1
Mathias Soeken 1
Bernard Diény 1
Chandan Sarkar 1
Nong Xiao 1
Fang Liu 1
Rafael Maeda 1
Fernanda Kastensmidt 1
Yan Fang 1
Jian Zhang 1
Abdoulaye Gamatié 1
Alaeddin Aydiner 1
Chidhambaranathan R 1
Chirag Garg 1
Arnab Roy 1
Niraj Jha 1
Chenyuan Zhao 1
Yingyezhe Jin 1
Karsten Beckmann 1
Zahiruddin Alamgir 1
Wujie Wen 1
Chris Winstead 1
Ernst Oberortner 1
Tara Deans 1
Fatima Hadjam 1
Hanwu Chen 1
Joseph Horton 1
Andrew Ferraiuolo 1
Hanieh Mirzaei 1
Jiale Liang 1
S Wong 1
Elena Maftei 1
Bo Yuan 1
Bin Li 1
Mehdi Kamal 1
Andres Kwasinski 1
Naoya Tate 1
Carlotta Guiducci 1
Alejandro Schrott 1
Francesco Abate 1
Steven Watts 1
Mohamad Krounbi 1
Xiaoxia Wu 1
Anish Muttreja 1
Shriram Raghunathan 1
Sheyshi Lu 1
Chandrakant Patel 1
Cullen Bash 1
Susmit Biswas 1
Heba Saadeldeen 1
Ricardo Bianchini 1
Raymond Beausoleil 1
Xi Chen 1
Weikang Qian 1
Sai Chittamuru 1
Srinivas Desai 1
Sudeep Pasricha 1
Gaurav Rathi 1
Bo Yuan 1
Somnath Paul 1
Priyadarshini Panda 1
Hantao Huang 1
Sukyung Yoon 1
Soheil Salehi 1
Ronald Demara 1
Keith Britt 1
Yang Liu 1
Yousuke Takada 1
Shihhsien Kuo 1
Q Shi 1
Siva Narendra 1
Xiang Wei 1
Gianluca Piccinini 1
Dafine Ravelosona 1
Moonseok Kim 1
Davide Bertozzi 1
Christophe Layer 1
Abdullah Guler 1
Chao Chen 1
Wei Jiang 1
Haoran Li 1
Zoha Pajouhi 1
Guangjun Wen 1
Anderson Sartor 1
Kaitak Lam 1
Ajay Singhvi 1
Leyla Nazhandali 1
Shengqi Yang 1
Jamil Wakil 1
Robert Hannon 1
Yue Wu 1
Daniel Davids 1
Aditya Prasad 1
Mariam Momenzadeh 1
Jun Zeng 1
Graham Jullien 1
Rajeswari Devadoss 1
Kele Shen 1
Sarmishtha Ghoshal 1
Jing Xie 1
Benoit Chappet De Vangel 1
César Torres-Huitzil 1
Nikil Dutt 1
Cyrille Chavet 1
Pooria Yaghini 1
Nader Bagherzadeh 1
Chiahung Chien 1
Marco Tartagni 1
Dongjae Shin 1
Minkyu Maeng 1
Luis Plana 1
David Clark 1
Jim Garside 1
Eustace Painkras 1
Evan Lent 1
Marc Jaekel 1
Domenico Cotroneo 1
Jin Sun 1
Vandi Alves 1
Jamie Collier 1
Clemens Moser 1
Rita Casadio 1
Bulent Kurdi 1
Dharmendra Modha 1
Geoffrey Burr 1
Sri Choday 1
Yiran Chen 1
Jun Yang 1
Alexey Khvalkovskiy 1
Tsungching Huang 1
Aditya Bansal 1
Paul Falkenstern 1
Mohamad Sawan 1
Jing Guo 1
Sophiane Senni 1

Affiliation Paper Counts
Universite Pierre et Marie Curie 1
University of Victoria 1
Feng Chia University 1
Southeast University China, Nanjing 1
City University of New York 1
Yangzhou University 1
University of Kansas 1
Centre Hospitalier de L'Universite de Montreal 1
Minia University 1
The University of British Columbia 1
Samsung Group 1
State University of New York at New Paltz 1
Ohio University Athens 1
Nanzan University 1
Air Force Research Laboratory Information Directorate 1
University of Texas at Austin 1
INRIA Institut National de Rechereche en Informatique et en Automatique 1
Brno University of Technology 1
Indian Institute of Science, Bangalore 1
University of Waterloo 1
University of Maryland, Baltimore 1
Peking University 1
Defence Research and Development Organisation India 1
Japan Science and Technology Agency 1
Zurich University of Applied Sciences Winterthur 1
Yeditepe University 1
National University of Singapore 1
University of Houston-Clear Lake 1
Harbin Institute of Technology 1
Chang Gung University 1
University of Twente 1
Chongqing University 1
University of North Texas 1
University of California, Berkeley 1
Shanghai Jiaotong University 1
Azusa Pacific University 1
Valparaiso University 1
Broadcom Corporation 1
University of Oxford 1
Federal University of Piaui 1
Cadence Design Systems 1
Research Organization of Information and Systems National Institute of Informatics 1
Wuhan University 1
Chung Yuan Christian University 1
Rutgers, The State University of New Jersey 1
Hiroshima University 1
University of Copenhagen 1
University of California System 1
NEC Corporation 1
Utah State University 1
Universite Nice Sophia Antipolis 1
Texas Instruments (India) Ltd 1
National Taiwan University Hospital 1
Amazon.com, Inc. 1
Ozyegin University 1
ORT Braude - College of Engineering 1
ARM Ltd. 1
Kalyani Government Engineering College 1
MCKV Institute of Engineering 1
NYU Tandon School of Engineering 1
Amity University, Kolkata 1
Universidad Catolica de Murcia 1
University of Calgary 2
Harbin Engineering University 2
Google Inc. 2
University of Turku 2
University of Missouri-Kansas City 2
Commissariat a L'Energie Atomique CEA 2
Colorado State University 2
Harvard University 2
Qualcomm Incorporated 2
Federal University of Uberlandia 2
Florida International University 2
University of Southern California, Information Sciences Institute 2
Kirtland Air Force Base 2
Pontifical Catholic University of Rio Grande do Sul 2
Shahed University 2
Louis Stokes Cleveland VA Medical Center 2
Advanced Micro Devices, Inc. 2
University of Science and Technology of China 2
Hewlett-Packard Inc. 2
University of Bristol 2
Jadavpur University 2
Bahcesehir University 2
Johannes Kepler University Linz 2
STMicroelectronics 2
Southern Illinois University 2
University of Ferrara 2
Missouri University of Science and Technology 2
Daneshgahe Esfahan 2
Stony Brook University 2
Virginia Tech 2
University of Seoul 2
Oracle Corporation 2
California Institute of Technology 2
Hefei National Laboratory for Physical Sciences at Microscale 2
Universite de Lyon 2
Toshiba America Research, Inc 2
European Centre for Soft Computing 2
Universite de Lorrain 2
Indian Institute of Technology 2
George Washington University 3
Indian Institute of Technology, Kharagpur 3
Delft University of Technology 3
Louisiana State University 3
Technical University of Denmark 3
National Chiao Tung University Taiwan 3
Beihang University 3
University of Washington, Seattle 3
University of Tennessee, Knoxville 3
University of York 3
University of New Brunswick 3
Malaviya National Institute of Technology 3
NEC Laboratories America, Inc. 3
Air Force Research Laboratory 3
Texas A and M University System 3
University of Tehran 3
University of Delaware 3
University of Calcutta 3
Catholic University of Leuven, Leuven 3
Carnegie Mellon University 3
Institut des Nanotechnologies de Lyon 3
Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India 4
Polytechnic University of Timisoara 4
Tyndall National Institute at National University of Ireland, Cork 4
Royal Institute of Technology 4
University of Siena 4
University of Texas at Arlington 4
Universite de Bretagne-Sud 4
CEA LETI 4
University of Arizona 4
State University of New York at Albany 4
Yonsei University 4
George Mason University 4
Polytechnic School of Montreal 4
Technical University of Munich 4
IBM, USA 4
Shanghai University 4
Portland State University 4
Oak Ridge National Laboratory 4
University of Tokyo 4
University of Rochester 4
Columbia University 4
Universite de Rennes 1 4
University of California, San Diego 4
Federal University of Pernambuco 4
Ghent University 4
Karlsruhe Institute of Technology 4
Rice University 5
University of Minnesota System 5
Federal University of Rio Grande do Sul 5
Universitat Politecnica de Catalunya 5
University of Texas at Dallas 5
University of Catania 5
Seoul National University 5
University of Naples Federico II 5
National Tsing Hua University 5
Chinese Academy of Sciences 5
Texas A and M University 5
Massachusetts Institute of Technology 5
Pacific Northwest National Laboratory 5
Indian Statistical Institute, Kolkata 5
University of Alberta 5
Japan National Institute of Information and Communications Technology 5
National Institute of Technology, Durgapur 5
Case Western Reserve University 6
University of Texas at San Antonio 6
University of California, Irvine 6
University of California, Davis 6
National Cheng Kung University 6
New York University 6
University of Virginia 6
Politecnico di Milano 6
Universite Paris-Sud XI 6
University of Utah 6
University of Southern California 6
University of Electronic Science and Technology of China 7
Newcastle University, United Kingdom 7
Drexel University 7
Southern Illinois University at Carbondale 7
University of California, Riverside 7
SPINTEC - Spin in Electronics Research 7
University of Manchester 8
Arizona State University 8
Nanyang Technological University 8
University of Maryland, Baltimore County 8
Keio University 8
Korea Advanced Institute of Science & Technology 8
The Institute of Fundamental Electronics, Orsay 8
HP Labs 9
Brown University 9
Indian Institute of Technology, Madras 9
Swiss Federal Institute of Technology, Zurich 9
Indian Institute of Technology, Delhi 9
National Taiwan University 10
Cornell University 10
Laboratoire d'Informatique, de Robotique et de Microelectronique de Montpellier LIRMM 10
IBM Almaden Research Center 10
University of Florida 10
Texas Instruments 10
University of California, Los Angeles 10
Rochester Institute of Technology 11
Bremen University 11
University of Massachusetts Amherst 11
University of Central Florida 11
University Michigan Ann Arbor 11
University of Bologna 11
University of Minnesota Twin Cities 11
University of Colorado at Boulder 12
The University of North Carolina at Charlotte 12
Boston University 12
National University of Defense Technology China 12
Tsinghua University 12
University of Pittsburgh 13
IBM Thomas J. Watson Research Center 13
Stanford University 14
University of South Florida Tampa 15
Georgia Institute of Technology 15
Swiss Federal Institute of Technology, Lausanne 16
University of California, Santa Barbara 16
Northeastern University 17
Amirkabir University of Technology 19
Washington State University 20
Intel Corporation 21
Polytechnic Institute of Turin 23
University of Notre Dame 23
Pennsylvania State University 25
Hong Kong University of Science and Technology 27
University of Connecticut 30
Duke University 37
Purdue University 38
Princeton University 53

ACM Journal on Emerging Technologies in Computing Systems (JETC)
Archive


2018
Volume 14 Issue 1, March 2018

2017
Volume 13 Issue 4, August 2017
Volume 13 Issue 3, May 2017 Special Issue on Hardware and Algorithms for Learning On-a-chip and Special Issue on Alternative Computing Systems
Volume 13 Issue 2, March 2017 Special Issue on Nanoelectronic Circuit and System Design Methods for the Mobile Computing Era and Regular Papers

2016
Volume 13 Issue 1, December 2016 Special Issue on Secure and Trustworthy Computing
Volume 12 Issue 4, July 2016 Regular Papers

2015
Volume 12 Issue 3, September 2015 Special Issue on Cross-Layer System Design and Regular Papers
Volume 12 Issue 2, August 2015 Special Issue on Advances in Design of Ultra-Low Power Circuits and Systems in Emerging Technologies
Volume 12 Issue 1, July 2015
Volume 11 Issue 4, April 2015 Special Issues on Neuromorphic Computing and Emerging Many-Core Systems for Exascale Computing

2014
Volume 11 Issue 3, December 2014 Special Issue on Computational Synthetic Biology and Regular Papers
Volume 11 Issue 2, November 2014 Special Issue on Reversible Computation and Regular Papers
Volume 11 Issue 1, September 2014
Volume 10 Issue 4, May 2014
Volume 10 Issue 3, April 2014
Volume 10 Issue 2, February 2014
Volume 10 Issue 1, January 2014 Special Issue on Reliability and Device Degradation in Emerging Technologies and Special Issue on WoSAR 2011

2013
Volume 9 Issue 4, November 2013 Special Issue on Bioinformatics
Volume 9 Issue 3, September 2013
Volume 9 Issue 2, May 2013 Special issue on memory technologies
Volume 9 Issue 1, February 2013

2012
Volume 8 Issue 4, October 2012
Volume 8 Issue 3, August 2012
Volume 8 Issue 2, June 2012 Special Issue on Implantable Electronics
Volume 8 Issue 1, February 2012

2011
Volume 7 Issue 4, December 2011
Volume 7 Issue 3, August 2011
Volume 7 Issue 2, June 2011
Volume 7 Issue 1, January 2011

2010
Volume 6 Issue 4, December 2010
Volume 6 Issue 3, August 2010
Volume 6 Issue 2, June 2010
Volume 6 Issue 1, March 2010

2009
Volume 5 Issue 4, November 2009
Volume 5 Issue 3, August 2009
Volume 5 Issue 2, July 2009
Volume 5 Issue 1, January 2009

2008
Volume 4 Issue 4, October 2008
Volume 4 Issue 3, August 2008
Volume 4 Issue 2, April 2008
Volume 4 Issue 1, March 2008
Volume 3 Issue 4, January 2008

2007
Volume 3 Issue 3, November 2007
Volume 3 Issue 2, July 2007
Volume 3 Issue 1, April 2007

2006
Volume 2 Issue 4, October 2006
Volume 2 Issue 3, July 2006
Volume 2 Issue 2, April 2006
Volume 2 Issue 1, January 2006

2005
Volume 1 Issue 3, October 2005
Volume 1 Issue 2, July 2005
Volume 1 Issue 1, April 2005
 
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