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Reuse Distance-Based Probabilistic Cache Replacement

This article proposes Probabilistic Replacement Policy (PRP), a novel replacement policy that evicts the line with minimum estimated hit probability... (more)

MINIME-GPU

We introduce MINIME-GPU, a novel automated benchmark synthesis framework for graphics processing units (GPUs) that serves to speed up architectural simulation of modern GPU architectures. Our framework captures important characteristics of original GPU applications and generates synthetic GPU benchmarks using the Open Computing Language (OpenCL)... (more)

Scalable Energy Efficiency with Resilience for High Performance Computing Systems

Ever-growing performance of supercomputers nowadays brings demanding requirements of energy efficiency and resilience, due to rapidly expanding size... (more)

Tumbler

Schedulers used by modern OSs (e.g., Oracle Solaris 11™ and GNU/Linux) balance load by balancing the number of threads in run queues of different cores. While this approach is effective for a single CPU multicore system, we show that it can lead to a significant load imbalance across CPUs of a multi-CPU multicore system. Because different... (more)

Four Metrics to Evaluate Heterogeneous Multicores

Semiconductor device scaling has made single-ISA heterogeneous processors a reality. Heterogeneous processors contain a number of different CPU cores... (more)

SPCM

Phase Change Memory (PCM) devices are one of the known promising technologies to take the place of DRAM devices with the aim of overcoming the obstacles of reducing feature size and stopping ever growing amounts of leakage power. In exchange for providing high capacity, high density, and nonvolatility, PCM Multilevel Cells (MLCs) impose high write... (more)

Two-Level Hybrid Sampled Simulation of Multithreaded Applications

Sampled microarchitectural simulation of single-threaded applications is mature technology for over a decade now. Sampling multithreaded applications,... (more)

Integrated Mapping and Synthesis Techniques for Network-on-Chip Topologies with Express Channels

The addition of express channels to a traditional mesh network-on-chip (NoC) has emerged as a viable... (more)

PARSECSs

In this work, we show how parallel applications can be implemented efficiently using task parallelism. We also evaluate the benefits of such parallel paradigm with respect to other approaches. We use the PARSEC benchmark suite as our test bed, which includes applications representative of a wide... (more)

A Framework for Application-Guided Task Management on Heterogeneous Embedded Systems

In this article, we propose a general framework for fine-grain application-aware task management in heterogeneous embedded platforms, which allows... (more)

Managing Mismatches in Voltage Stacking with CoreUnfolding

Five percent to 25% of power could be wasted before it is delivered to the computational resources on a die, due to inefficiencies of voltage... (more)

FaultSim

As memory systems scale, maintaining their Reliability Availability and Serviceability (RAS) is becoming more complex. To make matters worse, recent studies of DRAM failures in data centers and supercomputer environments have highlighted that large-granularity failures are common in DRAM chips. Furthermore, the move toward 3D-stacked memories can... (more)

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About TACO

The ACM Transactions on Architecture and Code Optimization focuses on hardware, software, and systems research spanning the fields of computer architecture and code optimization. Articles that appear in TACO present new techniques and concepts or report on experiences and experiments with actual systems. Insights useful to computer architects, hardware or software developers, system designers and tool builders are emphasized.

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Forthcoming Articles

R-GPU: a Reconfigurable GPU Architecture

To improve performance and energy efficiency of contemporary GPUs, we introduce R-GPU: a reconfigurable GPU architecture with communicating cores. R-GPU adds the ability to a GPU to reorganize its cores in a reconfigurable network. In R-GPU data movement and control is implicit in the configuration of the network. Each core executes a fixed instruction, reducing instruction decode count and increasing energy efficiency. On a number of benchmarks an average performance improvement of 2.1X is shown. A power estimation shows that power consumption can be reduced by 6%, while area increases by 4%, leading to an energy consumption reduction of 55%.

Optimizing Indirect Branches in Dynamic Binary Translators

A significant factor in the performance of a dynamic binary translator is its handling of indirect branches. An indirect branch requires translating a source program counter address to a translated program counter address every time the branch is executed, can impose a serious runtime penalty if it is not handled efficiently. This paper present three novel techniques to improve the performance of indirect branch translation: predicting function returns using a return address stack, detecting and optimizing branch tables in translated code and an efficient and thread-safe hash table mechanism for generic indirect branch handling.

Examining and Reducing the Influence of Sampling Errors on Feedback-Driven Optimizations

Feedback-driven optimization (FDO) is an important component in mainstream compilers. This paper gives the first systematic study in how sampling rates affect the accuracy of collected profiles and how the accuracy correlates with the usefulness of the profile for modern FDO. By studying basic block and edge profiles for FDO in two mature compilers, it reveals several counter-intuitive observations. Through a detailed analysis, it identifies three types of sampling-caused errors that critically impair the quality of the profiles for FDO. It then introduces a simple way to rectify profiles based on the findings.

A Compiler Approach for Exploiting Partial SIMD Parallelism

Existing vectorization techniques are ineffective for loops that exhibit little loop-level parallelism but some limited superword-level parallelism (SLP). We show that effectively vectorizing such loops requires partial vector operations to be executed correctly and efficiently, where the degree of partial SIMD parallelism is smaller than the SIMD datapath width. We present a simple yet effective SLP compiler technique, called PAVER (PArtial VEctorizeR), to optimize such partially vectorizable loops. For a set of 9 C/C++/Fortran applications with partial SIMD parallelism, PAVER achieves significantly better kernel and whole-program speedups than LLVM on both Intel's AVX and ARM's NEON.

Dynamic Memory Balancing for Virtualization

Allocating memory dynamically for virtual machines (VMs) according to demands provides significant benefits and great challenges. Efficient memory resource management requires knowledge of the memory demands at runtime. To summarize current working set size (WSS) of a VM but also model the relationship between performance and target memory allocation size, a widely proposed approach is to construct a miss ratio curve for a VM, whose cost is nontrivial. This paper first introduces a low cost WSS tracking system with effective optimizations on data structures, we also propose a MEmory Balancer, which dynamically reallocates guest memory based on the predicted WSS.

Hardware Performance Counter-Based Malware Identification and Detection with Adaptive Compressive Sensing

Hardware Performance Counter-based runtime checking is an effective way to identify malicious behaviors of malware, and detect malicious modifications to a legitimate programs control-flow. To reduce the overhead at the monitored platforms which has limited storage and computing resources, we present a sample-locally-analyze-remotely technique. The sampled HPC data is sent to a remote server for checking. To minimize the I/O bandwidth required for transmission, the fine-grained HPC profiles are compressed into much smaller vectors with Compressive Sensing. The experimental results demonstrate an 80% I/O bandwidth reduction after applying Compressive Sensing, without compromising the detection and identification capabilities.

Building heterogeneous UVMs (unified virtual memories) without the overhead

This work proposes a novel scheme to facilitate heterogeneous systems with unified virtual memory. State-of-the-art proposals, implement coherence protocols for sequential consistency (SC) between CPU cores, and between devices. Such mechanisms introduce severe bottlenecks in the system; therefore we adopt the heterogeneous race-free (HRF) memory model. The use of HRF simplifies the coherency protocol and the GPU memory management unit (MMU). Our protocol optimizes CPU and GPU demands separately, with the GPU part being simpler while the CPU being more elaborate and latency-aware. We achieve 35% performance improvement (average) and 50% EDP reduction (25% energy) over the corresponding SC implementation.

Clustering-Based Selection for the Exploration of Compiler Optimization Sequences

Sequence of compiler optimizations can have a significant impact on the application performance achieved. As a vast Design Space Exploration (DSE) is a complex and time consuming task, several researchers investigated strategies to both select good optimization sequences and to reduce the exploration time. Here, we present a clustering-based DSE approach that explores the set resulting from the combination of optimizations previously suggested for clustered functions. Experimental results reveal that our approach achieved a significant reduction on the total exploration time of the search space (20x over a Genetic Algorithm-based approach), and important performance speedups (42% over the baseline).

Thread-aware Adaptive Prefetcher on Multicore Systems: Improving the Performance for Multithreaded Workloads

This article proposes a thread-aware self-tuning data prefetcher, which consists of three new components: 1) a self-tuning prefetcher that uses runtime feedback to dynamically adjust each threads data prefetching modes and arguments, 2) a filtering mechanism that informs the hardware about which prefetching requests can cause shared data invalidation and should be discarded, and 3) a limiter thread acceleration to estimate and accelerate the critical threads. On a set of multithreaded parallel benchmarks, our approach improves the performance of 64-core system by 13% and reduces the energy-delay product by 14% over a multi-mode prefetch baseline system.

Understanding and Mitigating Covert Channels Through Branch Predictors

Covert channels through shared processor resources provide secret communication between two malicious processes - the trojan and the spy. In this paper, we classify, analyze and compare covert channels through dynamic branch prediction units in modern processors. We compare contention-based channel, and the channel that is based on exploiting branch predictors residual state. We compare both channels in detail. We also propose a software-only mitigation technique that is based on randomizing the state of the predictor tables on context switches. We show that this protection can effectively close this type of covert channels with minimal impact on performance.

Power Efficient Hardware Transactional Memory: Dynamic Issue of Transactions

Transactional Memory (TM) is not just an academic interest any more as industry has started to adopt the idea in its commercial products. In this paper, we propose Dynamic Transaction Issue, a new scheme that can be easily implemented on top of existing HTM (Hardware TM) systems. Instead of wasting power in transaction aborts, Dynamic Transaction Issue puts a processor core into an idle state when there is a reasonable suspicion that the current transaction running on it will be aborted soon in the future.

Autotuning Runtime Specialization for Sparse Matrix-Vector Multiplication

Runtime specialization is used for optimizing programs based on partial information available only at run time. In this paper we apply auto-tuning on runtime specialization of Sparse Matrix-Vector Multiplication to predict a specialization method among several. In 91-96% of the predictions, either the best or the second best method is chosen. Predictions achieve average speedups that are very close to the speedups achievable when only the best methods are used. By using an efficient code generator and a reduced set of matrix features, we show the total runtime costs can be amortized to bring performance benefits for many real-world cases.

Boosting the Priority of Garbage: Scheduling Collection on Heterogeneous Multicore Processors

While hardware is evolving towards heterogeneous multicore architectures, modern software applications are increasingly written in managed languages. A key component of any managed runtime is the garbage collector. In this paper, we explore concurrent garbage collection's behavior, and how to schedule it on a heterogeneous system to optimize application performance. We develop a new, adaptive scheduling algorithm that responds to GC criticality signals from the managed runtime, giving more big core cycles to the concurrent collector when it is under pressure and in danger of suspending the application.

Bibliometrics

Publication Years 2004-2016
Publication Count 449
Citation Count 1454
Available for Download 449
Downloads (6 weeks) 3444
Downloads (12 Months) 26607
Downloads (cumulative) 175715
Average downloads per article 391
Average citations per article 3
First Name Last Name Award

First Name Last Name Paper Counts
Lieven Eeckhout 16
André Seznec 8
Rajiv Gupta 8
Yuan Xie 8
Bruce Childers 7
Kevin Skadron 7
Stijn Eyerman 7
Michael O'Boyle 6
Mateo Valero 6
David Gregg 6
Antonia Zhai 6
Margaret Martonosi 6
Norman Jouppi 6
Yan Solihin 5
Pen Yew 5
Haitham Akkary 5
Shlomo Weiss 5
Jun Yang 5
Weichung Hsu 5
Timothy Sherwood 5
Christian Wimmer 5
Laxmi Bhuyan 5
Jingling Xue 5
David Whalley 5
Antonio González 5
Onur Mutlu 5
Jaume Abella 5
Adrián Cristal 5
Tor Aamodt 4
Jack Davidson 4
Daniel Jiménez 4
Oğuz Ergin 4
Louis Pouchet 4
Milos Prvulovic 4
Henk Corporaal 4
Sarita Adve 4
Miquel Moretó 4
Osman Ünsal 4
Chengyong Wu 4
Christos Kozyrakis 4
Francisco Cazorla 4
Yu Du 4
Timothy Jones 4
David Brooks 4
Mateo Valero 4
Michael Spear 3
Jose Renau 3
Chialin Yang 3
Dmitry Ponomarev 3
Ponnuswamy Sadayappan 3
Walid Najjar 3
Ramón Doallo 3
Josep Torrellas 3
José Llabería 3
Ran Ginosar 3
Antoniu Pop 3
Rami Melhem 3
Chandra Krintz 3
Youtao Zhang 3
Prashant Nair 3
Marcelo Cintra 3
Daniel Mossé 3
Avi Mendelson 3
Yiannakis Sazeides 3
Rubén Titos-Gil 3
José García 3
Mahmut Kandemir 3
Frank Mueller 3
Mary Soffa 3
James Tuck 3
Jue Wang 3
Michael Franz 3
Hanspeter Mössenböck 3
Prasad Kulkarni 3
Víctor Viñals 3
Xiangyu Dong 3
María Garzarán 3
Kim Hazelwood 3
David Tarjan 3
Miao Zhou 3
Pierre Michaud 3
Todd Mowry 3
Hans Vandierendonck 3
Francky Catthoor 3
Moinuddin Qureshi 3
Lizy John 3
Basilio Fraguela 3
Wengfai Wong 3
Paolo Ienne 3
Aamer Jaleel 3
Yunji Chen 3
Shuangde Fang 3
Motohiro Kawahito 2
Sebastian Hack 2
Betul Buyukkurt 2
Rupesh Nasre 2
Gennady Pekhimenko 2
Zhibin Yu 2
Xiaofei Liao 2
Yuanjie Huang 2
Lishiuan Peh 2
José Martínez 2
Changhui Lin 2
Guyeon Wei 2
Jorge Albericio 2
Alex Jones 2
Olivier Temam 2
Jagannathan Ramanujam 2
Zheng Wang 2
Michael Smith 2
Stefan Brunthaler 2
Ron Gabor 2
Jin Lin 2
Dean Tullsen 2
Neil Vachharajani 2
Bjorn De Sutter 2
Yunheung Paek 2
Wim Heirman 2
Ben Juurlink 2
Shashidhar Mysore 2
Magnus Själander 2
Fabrice Rastello 2
Albert Cohen 2
Leonid Yavits 2
Sanyam Mehta 2
Angeliki Kritikakou 2
Philippe Clauss 2
Christophe Dubach 2
Olivier Temam 2
Stefanos Kaxiras 2
Alex Ramírez 2
Jason Hiser 2
Jianjun Li 2
David August 2
Simon Steely 2
Anurag Negi 2
Ramesh Karri 2
Nathanael Premillieu 2
Venmugil Elango 2
Wenjia Ruan 2
Scott Mahlke 2
Chuntao Jiang 2
Nael Abu-Ghazaleh 2
Gabriel Loh 2
Bronis De Supinski 2
Tinfook Ngai 2
Hwansoo Han 2
Min Feng 2
Xuejun Yang 2
William Hasenplaugh 2
Alberto Ros 2
Sven Verdoolaege 2
Morteza Kafshdooz 2
Alireza Ejlali 2
Uday Bondhugula 2
Quan Chen 2
Xiaobing Feng 2
John Kim 2
Cedric Nugteren 2
Maximilien Breughe 2
Michael O’boyle 2
Glenn Reinman 2
Grigori Fursin 2
Jacob Leverich 2
Karthik Sankaranarayanan 2
Frederic Chong 2
Komal Jothi 2
Yuanyuan Zhou 2
Abhishek Bhattacharjee 2
Manlap Li 2
Joel Emer 2
Banit Agrawal 2
Yong Li 2
Doug Simon 2
Yang Chen 2
Mary Irwin 2
Gautham Beeraka 2
Mauricio Álvarez-Mesa 2
Joseph Sharkey 2
Todd Austin 2
Edwin Bonilla 2
Marco Santambrogio 2
Kishore Pusukuri 2
Amit Golander 2
Diego Andrade 2
Ravishankar Iyer 2
Li Zhao 2
Yangchun Luo 2
Mageda Sharafeddine 2
Bart Coppens 2
Pablo Ibáñez 2
Michela Becchi 2
Arun Kanuparthi 2
Yosi Asher 2
Rajkishore Barik 2
Yuanshin Hwang 2
Jason Loew 2
Costas Goutis 2
Per Larsen 2
David Roberts 2
Chuanjun Zhang 2
Oliverio Santana 2
Chenggang Wu 2
Jason Cong 2
Trevor Carlson 2
Jungho Ahn 2
Ghassan Shobaki 2
Naveen Muralimanohar 2
Amir Morad 2
Xiangyu Dong 2
Vasilios Kelefouras 2
Qixiao Liu 2
Roy Ju 2
Guru Venkataramani 2
Ram Rangan 2
Ibrahim Hur 2
Erven Rohou 2
Karthikeyan Sankaralingam 2
Dongrui She 1
Zhiying Wang 1
Quentin Colombet 1
Florian Brandner 1
Paraskevas Evripidou 1
Efraim Rotem 1
Patrick Eitschberger 1
Gabriel Rodríguez 1
Juan Touriño 1
Cristóbal Camarero 1
David Padua 1
Dan He 1
Vivek Seshadri 1
Amnon Barak 1
Tal Ben-Nun 1
Ramón Beivide 1
Magnus Jahre 1
J Ramanujam 1
Ananta Tiwari 1
Lee Howes 1
Yujie Liu 1
Johannes Doerfert 1
Olivier Rochecouste 1
John Cortes 1
Mojtaba Mehrara 1
Hideho Arakida 1
Haiming Liu 1
Hugh Leather 1
Licheng Chen 1
Mingyu Chen 1
Eric Seckler 1
Gulfem Savrun-Yeniceri 1
Etem Deniz 1
Avinash Malik 1
Shahar Kvatinsky 1
Zonglin Liu 1
Subhasis Das 1
Lizhong Chen 1
Woojin Choi 1
Donatella Sciuto 1
Yeoul Na 1
Marc Casas 1
Eduard Ayguadé 1
Saugata Ghose 1
Janjan Wu 1
Abdullah Kayi 1
Pekka Jääskeläinen 1
Michal Wegiel 1
Weifeng Xu 1
Shyhtsunfelix Wu 1
Jedidiah Crandall 1
Shiwen Hu 1
Brett Brotherton 1
Lin Tan 1
Hussam Mousa 1
Salvador Petit 1
Bin Li 1
Dongrui Fan 1
Srikanth Srinivasan 1
Ryan Kastner 1
Kanad Ghose 1
Luis Ceze 1
David Kaeli 1
Xi Li 1
Junneng Zhang 1
Kiyoung Choi 1
Jian Li 1
Ram Rajamony 1
Nectarios Koziris 1
Jason Mars 1
YenMing Chen 1
Hyunjin Lee 1
Robert Bell 1
R Rakvic 1
Jeffery Von Ronne 1
Benoît Meister 1
Andreas Lankes 1
Andreas Herkersdorf 1
Valeria Bertacco 1
Anil Krishna 1
Gyungsu Byun 1
Glenn Reinman 1
Zhenjiang Wang 1
Leonid Domnitser 1
Sabih Gerez 1
Manuel Acacio 1
Wolfgang Karl 1
Guang Gao 1
Tong Wu 1
Donghyuk Woo 1
Hsien Lee 1
Stefano Carlo 1
Davide Bertozzi 1
Toshio Nakatani 1
Avinash Malik 1
Eran Shifer 1
Jinbo Xu 1
Jie Zhou 1
Jan Martinsen 1
Anders Isberg 1
Radu Teodorescu 1
Martin Kong 1
Ramaswamy Govindarajan 1
Enrique Vallejo 1
Wei Tong 1
Helge Bahmann 1
Nico Reissmann 1
Dominik Grewe 1
David Ham 1
Laura Carrington 1
Ali Jannesari 1
Mihail Popov 1
William Jalby 1
Naghmeh Karimi 1
Xueyang Wang 1
Ozgur Sinanoglu 1
Beayna Grigorian 1
Rongguey Chang 1
Nitya Ranganathan 1
Doug Burger 1
Charles Moore 1
Yatish Patel 1
Dean Copsey 1
Narayanan Vijaykrishnan 1
Zehan Cui 1
Lei Liu 1
Mingyu Chen 1
Huahan Zhang 1
Preeti Panda 1
Georgios Tournavitis 1
Christian Häubl 1
Hamid Sarbazi-Azad 1
Y Srikant 1
William Dally 1
Ehsan Ardestani 1
Zizhong Chen 1
Heikki Kultala 1
Hui Feng 1
Jaydeep Marathe 1
Irshad Pananilath 1
Bharath Swamy 1
Rajesh Gupta 1
Hsiangyun Cheng 1
Robin Paul 1
Najm Rmaileh 1
Yazhuo Dong 1
Hongjian Li 1
Libo Huang 1
Jungho Ahn 1
George Matheou 1
Simon Moll 1
Rakesh Komuravelli 1
Hongyi Xin 1
Ely Levy 1
Zhenman Fang 1
Binyu Zang 1
Fabio Luporini 1
Ana Varbanescu 1
Florian Rathgeber 1
Roy Campbell 1
Zia Huda 1
Chiehting Huang 1
Vineeth Mekkat 1
Jinho Suh 1
Ahmad Zmily 1
Tzongyen Lin 1
Stephen Keckler 1
Yuan Ruan 1
Wei Zhang 1
Chiachen Chou 1
Thomas Carle 1
Mohammad Arjomand 1
Shuming Chen 1
Venkata Tavva 1
Rakesh Kumar 1
Nisheeth Shrivastava 1
Thomas Conte 1
Martin Schulz 1
Richard Strong 1
Ivan Sham 1
Ioannis Doudalis 1
Jinseong Jeon 1
Brian Fields 1
Kristof Du Bois 1
Huimin Cui 1
Albert Cohen 1
Jimmy Cleary 1
Mark Purcell 1
Pablo Abad 1
Suresh Purini 1
Fabien Coelho 1
Chun Chen 1
Murray Cole 1
Mick Jordan 1
Servesh Muralidharan 1
Ehsan Totoni 1
Albert Cohen 1
Andrei Hagiescu 1
Ioannis Sourdis 1
Sergei Dyshel 1
Marcel Zalmanovici 1
Zhao Zhang 1
Daniel Jiménez-González 1
Bin Ren 1
Deyu Shen 1
Bernhard Urban 1
Lukas Stadler 1
Naifeng Jing 1
Wei Shu 1
Minyou Wu 1
Xiaoyao Liang 1
Ivan Stalev 1
Pradip Valathol 1
Jaikrishnan Menon 1
Gabriel Southern 1
Yongwen Wang 1
Zheng Wang 1
Håkan Grahn 1
Xing Zhou 1
Lei Jiang 1
Tim Harris 1
Tao Li 1
Esther Salamí 1
Fei Guo 1
Xiaoxia Wu 1
Sanjeev Kumar 1
Xicheng Lu 1
Gen Li 1
Bin Liu 1
Wolfram Amme 1
Jaejin Lee 1
Stefan Wallentowitz 1
Michael Orshansky 1
Noel Eisley 1
Jia Yu 1
Vincenzo Catania 1
Maurizio Palesi 1
Carlo Sicignano 1
Smruti Sarangi 1
Seonwook Kim 1
Li Tan 1
Dimitrios Chasapis 1
Jesús Labarta 1
Francisco Gaspar 1
Dingyong Hong 1
Tomi Aijo 1
Russell Tessier 1
Dee Weikle 1
Xiaodong Li 1
Gerd Ascheid 1
Pin Zhou 1
Polychronis Xekalakis 1
Nikolas Ioannou 1
Chienhao Lee 1
Ruth Bahar 1
Douglas Clark 1
Josep Larriba-Pey 1
Bo Zhao 1
Kyuseung Han 1
Douglas Jones 1
Christopher Hughes 1
Yujung Cheng 1
Ying Zhang 1
Xudong Fang 1
Wei Lin 1
Qiong Cai 1
Daniel Sorin 1
Fuxin Zhang 1
Yu Chen 1
Soojung Ryu 1
Kevin Stock 1
Ponuswamy Sadayappan 1
Sven Reinemo 1
Lois Orosa 1
Zhenhao Pan 1
Arnaud Grasset 1
Felipe Cabarcas 1
Carlos Villavieja 1
Milan Pavlovic 1
Yoav Etsion 1
Selma Saidi 1
Thierry Lepley 1
Fabian Nowak 1
Qingping Wang 1
Per Stenström 1
Jingfei Kong 1
Huiyang Zhou 1
Georgios Varsamopoulos 1
Chen Cher 1
Gilberto Contreras 1
Kypros Constantinides 1
Eric Debes 1
Yenkuang Chen 1
Benoít Dupont De Dinechin 1
Yuliu Chen 1
Jongeun Lee 1
Gerard Smit 1
Stijn Polfliet 1
Avinoam Kolodny 1
Alejandro Rico 1
Farrukh Hijaz 1
Pradeep Ramachandran 1
Siva Hari 1
Piero Olivo 1
Stamatis Vassiliadis 1
J Steffan 1
Saurabh Sharma 1
Karan Singh 1
Sally McKee 1
Wei Zhang 1
Rong Chen 1
Daofu Liu 1
Chengkok Koh 1
Yiran Chen 1
Hai Li 1
Brian Rogers 1
Jonas Maebe 1
Owen Callanan 1
Jacqueline Chame 1
Ozcan Ozturk 1
Greg Brown 1
John Wernsing 1
Kyoungwoo Lee 1
Bita Mazloom 1
Walid Ghandour 1
Zhijia Zhao 1
Narasimha Reddy 1
Paul Gratz 1
Vivek Sarkar 1
Hai Jin 1
Lieven Eeckhout 1
Xiaowen Chen 1
Sandeep D'souza 1
Vijay Nagarajan 1
Giuseppe Natale 1
Kevin Chang 1
Erik Tomusk 1
Luis Tanica 1
Chengyi Chou 1
Ryan Riley 1
Olivier Serres 1
Tarek El-Ghazawi 1
Mohammadkazem Taram 1
Weijia Li 1
Martin Burtscher 1
Ilya Ganusov 1
Michele Co 1
Chris Bentley 1
Koen De Bosschere 1
Brad Calder 1
Heinrich Meyr 1
James Geraci 1
Adam Lewis 1
Soumik Ghosh 1
Yang Yang 1
Alex Aletà 1
Evan Speight 1
Pohan Wang 1
Chen Tian 1
Guilherme Ottoni 1
Davide Patti 1
Colin Blundell 1
Guibin Wang 1
Vijay Reddi 1
Andrei Terechko 1
Zahra Abbasi 1
Eren Kursun 1
Ning Weng 1
Ruchira Sasanka 1
Guang Gao 1
Alban Douillet 1
Jiajhe Li 1
Di Xu 1
Ramakrishna Upadrasta 1
Elisardo Antelo 1
Tom Bruintjes 1
Bert Molenkamp 1
Sami Yehia 1
George Patsilaras 1
Benoît Pradelle 1
Michael Lyons 1
Mark Hempstead 1
Elkin Garcia 1
Daniel Sánchez 1
Xiuyi Zhou 1
Alvinwy Su 1
Emrah Islek 1
Miguel Gonzalez-Mesa 1
Davide Bartolini 1
Donatella Sciuto 1
Rodolfo Neuber 1
Christopher Colohan 1
Thomas Rodriguez 1
Jian Li 1
Francis Lau 1
Haibo Chen 1
Ling Li 1
Patrick Crowley 1
Keoncheol Shin 1
Fen Xie 1
Rastislav Bodík 1
Chris Newburn 1
Mark Hill 1
Tong Chen 1
Xiaobing Feng 1
Christian Tenllado 1
François Irigoin 1
Riyadh Baghdadi 1
Protonu Basu 1
Boubacar Diouf 1
Can Hantas 1
Albert Cohen 1
Yuanchun Shi 1
Laurent Daynès 1
Li Wang 1
Jaekyu Lee 1
Tanima Dey 1
Wei Wang 1
Peter Gavin 1
Shengde Wang 1
Viacheslav Fedorov 1
Víctor Jiménez 1
R Ramanathan 1
Rubén Gran 1
Ali Bayrak 1
Nikola Velickovic 1
Wayne Burleson 1
Fei Wu 1
Deke Guo 1
Fangyuan Chen 1
Filippo Sironi 1
Ravi Kasha 1
Madhu Mutyam 1
David Albonesi 1
Zhi Guo 1
Kenneth Russell 1
Christopher Healy 1
Rich Caruana 1
George Reis 1
Wilson Fung 1
Zhichao Yan 1
Yujuan Tan 1
Doris Chen 1
Panagiotis Dagritzikos 1
Albert Cohen 1
Kevin Williams 1
Marco Gerards 1
Thibaut Lutz 1
Leonel Sousa 1
Stefano Crespi Reghizzi 1
Jongwon Lee 1
Xipeng Shen 1
Mert Dikmen 1
Guangyu Sun 1
Bogdan Prisacari 1
Torsten Hoefler 1
Chengzhong Xu 1
Thejas Ramashekar 1
Srdjan Stipić 1
Mahesh Ravishankar 1
Alen Bardizbanyan 1
Samantika Subramaniam 1
Xiaolin Wang 1
Chrysostomos Nicopoulos 1
Puneet Gupta 1
Shankar Balachandran 1
Jishen Zhao 1
Darío Gracia 1
Alexandra Ferrerón 1
Frederick Ryckbosch 1
Roman Malits 1
Eduardo Quiñones 1
Pranav Tendulkar 1
Mario Kicherer 1
Koen De Bosschere 1
George Michelogiannakis 1
Omer Khan 1
Eladio Gutiérrez 1
Andi Drebes 1
Jonathan Winter 1
Peng Liu 1
Thomas Kotzmann 1
Wankang Zhao 1
Kevin Casey 1
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Affiliation Paper Counts
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VMware, Inc 1
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Cray Inc. 1
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Freescale Semiconductor 1
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LG 1
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NXP Semiconductors 1
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Friedrich Schiller University Jena 1
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National University of Sciences and Technology Pakistan 1
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Korean Agency for Defense Development 1
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International Institute of Information Technology Hyderabad 2
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Instituto Superior Tecnico 2
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Commissariat a L'Energie Atomique CEA 2
Altera Corporation 2
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Verimag 2
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ARM Ltd. 2
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Google Inc. 3
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Thales 3
IBM 3
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Microsoft Research 4
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Duke University 5
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IBM Thomas J. Watson Research Center 5
NEC Laboratories America, Inc. 5
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Advanced Micro Devices, Inc. 8
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University of Cyprus 8
The University of British Columbia 9
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Ecole Normale Superieure 10
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Cornell University 11
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Politecnico di Milano 11
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INRIA Institut National de Rechereche en Informatique et en Automatique 12
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Seoul National University 14
Institute of Computing Technology Chinese Academy of Sciences 14
National Taiwan University 15
IBM Research 15
American University of Beirut 15
HP Labs 16
Institut de Recherche en Informatique et Systemes Aleatoires 16
University of California, Irvine 17
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University of Texas at Austin 17
Ohio State University 18
Barcelona Supercomputing Center 18
Shanghai Jiaotong University 19
Georgia Institute of Technology 22
Carnegie Mellon University 23
University of California, Santa Barbara 24
North Carolina State University 25
Pennsylvania State University 26
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University of Illinois at Urbana-Champaign 28
National University of Defense Technology China 29
Chinese Academy of Sciences 35
University of Virginia 36
University of California, Riverside 38
University of Pittsburgh 44
Ghent University 46
Universitat Politecnica de Catalunya 54
Intel Corporation 58

ACM Transactions on Architecture and Code Optimization (TACO)
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