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ORCID52nd MICRO 2019: Columbus, OH, USA
- Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2019, Columbus, OH, USA, October 12-16, 2019. ACM 2019, ISBN 978-1-4503-6938-1
Accelerators for Machine Learning
- Sumanth Gudaparthi, Surya Narayanan, Rajeev Balasubramonian, Edouard Giacomin
, Hari Kambalasubramanyam, Pierre-Emmanuel Gaillardon:
Wire-Aware Architecture and Dataflow for CNN Accelerators. 1-13 - Yakun Sophia Shao, Jason Clemons, Rangharajan Venkatesan, Brian Zimmer, Matthew Fojtik, Nan Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Ross Pinckney, Priyanka Raina, Stephen G. Tell, Yanqing Zhang, William J. Dally, Joel S. Emer, C. Thomas Gray, Brucek Khailany, Stephen W. Keckler:
Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture. 14-27 - Alberto Delmas Lascorz, Sayeh Sharify, Isak Edo Vivancos, Dylan Malone Stuart, Omar Mohamed Awad, Patrick Judd, Mostafa Mahmoud, Milos Nikolic, Kevin Siu, Zissis Poulos, Andreas Moshovos:
ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning. 28-41
Security 1
- Thomas Bourgeat, Ilia A. Lebedev, Andrew Wright, Sizhuo Zhang, Arvind, Srinivas Devadas:
MI6: Secure Enclaves in a Speculative Out-of-Order Processor. 42-56 - Austin Harris, Shijia Wei, Prateek Sahu, Pranav Kumar, Todd M. Austin, Mohit Tiwari:
Cyclone: Detecting Contention-Based Cache Information Leaks Through Cyclic Interference. 57-72 - Gururaj Saileshwar, Moinuddin K. Qureshi:
CleanupSpec: An "Undo" Approach to Safe Speculation. 73-86
In/Near Memory Computing 1
- Elaheh Sadredini, Reza Rahimi, Vaibhav Verma, Mircea Stan, Kevin Skadron:
eAP: A Scalable and Efficient In-Memory Accelerator for Automata Processing. 87-99 - Fei Gao, Georgios Tziantzioulis, David Wentzlaff:
ComputeDRAM: In-Memory Compute Using Off-the-Shelf DRAMs. 100-113 - Teyuh Chou, Wei Tang, Jacob Botimer, Zhengya Zhang:
CASCADE: Connecting RRAMs to Extend Analog Dataflow In An End-To-End In-Memory Processing Paradigm. 114-125
Accelerators for Machine Learning 2
- Berkin Akin, Zeshan A. Chishti, Alaa R. Alameldeen:
ZCOMP: Reducing DNN Cross-Layer Memory Footprint Using Vector Extensions. 126-138 - Weizhe Hua, Yuan Zhou, Christopher De Sa, Zhiru Zhang, G. Edward Suh:
Boosting the Performance of CNN Accelerators with Dynamic Fine-Grained Channel Gating. 139-150 - Ashish Gondimalla, Noah Chesnut, Mithuna Thottethodi, T. N. Vijaykumar:
SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks. 151-165 - Skanda Koppula, Lois Orosa, Abdullah Giray Yaglikçi, Roknoddin Azizi, Taha Shahroodi, Konstantinos Kanellopoulos, Onur Mutlu:
EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM. 166-181 - Chao-Tsung Huang, Yu-Chun Ding, Huan-Ching Wang, Chi-Wen Weng, Kai-Ping Lin, Li-Wei Wang, Li-De Chen:
eCNN: A Block-Based and Highly-Parallel CNN Accelerator for Edge Inference. 182-195
Storage Systems
- Yu-Ching Hu, Murtuza Taher Lokhandwala, Te I, Hung-Wei Tseng:
Dynamic Multi-Resolution Data Storage. 196-210 - Youngseop Shim, Myungsuk Kim, Myoungjun Chun, Jisung Park, Yoona Kim, Jihong Kim:
Exploiting Process Similarity of 3D Flash Memory for High Performance SSDs. 211-223 - Vikram Sharma Mailthody, Zaid Qureshi, Weixin Liang, Ziyan Feng, Simon Garcia De Gonzalo, Youjie Li, Hubertus Franke, Jinjun Xiong, Jian Huang, Wen-Mei Hwu:
DeepStore: In-Storage Acceleration for Intelligent Queries. 224-238 - Mohammadamin Ajdari, Wonsik Lee, Pyeongsu Park, Joonsung Kim, Jangwoo Kim:
FIDR: A Scalable Storage System for Fine-Grain Inline Data Reduction with Efficient Memory Handling. 239-252
Quantum Computing
- Swamit S. Tannu, Moinuddin K. Qureshi:
Ensemble of Diverse Mappings: Improving Reliability of Quantum Computers by Orchestrating Dissimilar Mistakes. 253-265 - Pranav Gokhale, Yongshan Ding, Thomas Propson, Christopher Winkler, Nelson Leung, Yunong Shi, David I. Schuster, Henry Hoffmann, Frederic T. Chong:
Partial Compilation of Variational Algorithms for Noisy Intermediate-Scale Quantum Machines. 266-278 - Swamit S. Tannu, Moinuddin K. Qureshi:
Mitigating Measurement Errors in Quantum Computers by Exploiting State-Dependent Bias. 279-290 - Poulami Das, Swamit S. Tannu, Prashant J. Nair, Moinuddin K. Qureshi:
A Case for Multi-Programming Quantum Computers. 291-303
Accelerators for Emerging Applications
- Eunjin Baek, Hunjun Lee, Youngsok Kim, Jangwoo Kim:
FlexLearn: Fast and Highly Efficient Brain Simulations Using Flexible On-Chip Learning. 304-318 - Kartik Hegde, Hadi Asghari Moghaddam, Michael Pellauer, Neal Clayton Crago, Aamer Jaleel, Edgar Solomonik, Joel S. Emer, Christopher W. Fletcher:
ExTensor: An Accelerator for Sparse Tensor Algebra. 319-333 - Anirban Nag, C. N. Ramachandra, Rajeev Balasubramonian, Ryan Stutsman, Edouard Giacomin, Hari Kambalasubramanyam, Pierre-Emmanuel Gaillardon:
GenCache: Leveraging In-Cache Operators for Efficient Sequence Alignment. 334-346 - Fazle Sadi, Joe Sweeney, Tze Meng Low, James C. Hoe, Larry T. Pileggi, Franz Franchetti:
Efficient SpMV Operation for Large and Highly Sparse Matrices using Scalable Multi-way Merge Parallelization. 347-358
GPGPUs & Heterogeneous Architectures
- Maohua Zhu, Tao Zhang, Zhenyu Gu, Yuan Xie:
Sparse Tensor Core: Algorithm and Hardware Co-Design for Vector-wise Sparse Neural Networks on Modern GPUs. 359-371 - Oreste Villa, Mark Stephenson, David W. Nellans, Stephen W. Keckler:
NVBit: A Dynamic Binary Instrumentation Framework for NVIDIA GPUs. 372-383 - Raghavendra Pradyumna Pothukuchi, Joseph L. Greathouse, Karthik Rao, Christopher Erb, Leonardo Piga, Petros G. Voulgaris, Josep Torrellas:
Tangram: Integrated Control of Heterogeneous Computers. 384-398 - Jongouk Choi, Qingrui Liu, Changhee Jung:
CoSpec: Compiler Directed Speculative Intermittent Computation. 399-412
Caching
- Zhan Shi, Xiangru Huang, Akanksha Jain, Calvin Lin:
Applying Deep Learning to the Cache Replacement Problem. 413-425 - Ziqiang Huang, José A. Joao, Alejandro Rico, Andrew D. Hilton, Benjamin C. Lee:
DynaSprint: Microarchitectural Sprints with Dynamic Utility and Thermal Management. 426-439 - Guowei Zhang, Daniel Sánchez:
Leveraging Caches to Accelerate Hash Tables and Memoization. 440-452 - Seokin Hong, Bülent Abali, Alper Buyuktosunoglu, Michael B. Healy, Prashant J. Nair:
Touché: Towards Ideal and Efficient Cache Compression By Mitigating Tag Area Overheads. 453-465
Emerging Memory & Storage Technology
- Siddharth Gupta, Alexandros Daglis, Babak Falsafi:
Distributed Logless Atomic Durability with Persistent Memory. 466-478 - Pengfei Zuo, Yu Hua, Yuan Xie:
SuperMem: Enabling Application-transparent Secure Persistent Memory with Low Overheads. 479-492 - Congming Gao, Min Ye, Qiao Li, Chun Jason Xue, Youtao Zhang, Liang Shi, Jun Yang:
Constructing Large, Durable and Fast SSD System via Reprogramming 3D TLC Flash Memory. 493-505
Microarchitecture
- Hideki Ando:
SWQUE: A Mode Switching Issue Queue with Priority-Correcting Circular Queue. 506-518 - Niranjan Soundararajan, Saurabh Gupta, Ragavendra Natarajan, Jared Stark, Rahul Pal, Franck Sala, Lihu Rappoport, Adi Yoaz, Sreenivas Subramoney:
Towards the adoption of Local Branch Predictors in Modern Out-of-Order Superscalar Processors. 519-530 - Rahul Bera, Anant V. Nori, Onur Mutlu, Sreenivas Subramoney:
DSPatch: Dual Spatial Pattern Prefetcher. 531-544
Security 2
- Hongyan Xia, Jonathan Woodruff, Sam Ainsworth, Nathaniel Wesley Filardo, Michael Roe, Alexander Richardson, Peter Rugg, Peter G. Neumann, Simon W. Moore, Robert N. M. Watson, Timothy M. Jones:
CHERIvoke: Characterising Pointer Revocation using CHERI Capabilities for Temporal Memory Safety. 545-557 - Hiroshi Sasaki, Miguel A. Arroyo, M. Tarek Ibn Ziad, Koustubha Bhat, Kanad Sinha, Simha Sethumadhavan:
Practical Byte-Granular Memory Blacklisting using Califorms. 558-571 - Ofir Weisse, Ian Neal, Kevin Loughlin, Thomas F. Wenisch, Baris Kasikci:
NDA: Preventing Speculative Execution Attacks at Their Source. 572-586
Domain Specific Accelerators
- Wenqin Huangfu, Xueqi Li, Shuangchen Li, Xing Hu, Peng Gu, Yuan Xie:
MEDAL: Scalable DIMM based Near Data Processing Accelerator for DNA Seeding Algorithm. 587-599 - Konstantinos Kanellopoulos, Nandita Vijaykumar, Christina Giannoula, Roknoddin Azizi, Skanda Koppula, Nika Mansouri-Ghiasi, Taha Shahroodi, Juan Gómez-Luna, Onur Mutlu:
SMASH: Co-designing Software Compression and Hardware-Accelerated Indexing for Efficient Sparse Matrix Operations. 600-614 - Mingyu Yan, Xing Hu, Shuangchen Li, Abanti Basak, Han Li, Xin Ma, Itir Akgun, Yujing Feng, Peng Gu, Lei Deng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, Yuan Xie:
Alleviating Irregularity in Graph Analytics Acceleration: a Hardware/Software Co-Design Approach. 615-628 - Tiancheng Xu, Boyuan Tian, Yuhao Zhu:
Tigris: Architecture and Algorithms for 3D Perception in Point Clouds. 629-642
Mobile and Embedded Architectures
- Yu Feng, Paul N. Whatmough, Yuhao Zhu:
ASV: Accelerated Stereo Vision System. 643-656 - Haibo Zhang, Shulin Zhao, Ashutosh Pattnaik, Mahmut T. Kandemir, Anand Sivasubramaniam, Chita R. Das:
Distilling the Essence of Raw Video to Reduce Memory Usage and Energy at Edge Devices. 657-669 - Graham Gobieski, Amolak Nagi, Nathan Serafin, Mehmet Meric Isgenc, Nathan Beckmann, Brandon Lucia:
MANIC: A Vector-Dataflow Architecture for Ultra-Low-Power Embedded Systems. 670-684 - Bryan Donyanavard, Tiago Mück, Amir M. Rahmani, Nikil D. Dutt, Armin Sadighi, Florian Maurer, Andreas Herkersdorf:
SOSA: Self-Optimizing Learning with Self-Adaptive Control for Hierarchical System-on-Chip Management. 685-698
In/Near Memory Computing 2
- Mohammad Alian, Nam Sung Kim:
NetDIMM: Low-Latency Near-Memory Network Interface Architecture. 699-711 - Youwei Zhuo, Chao Wang, Mingxing Zhang, Rui Wang, Dimin Niu, Yanzhi Wang, Xuehai Qian:
GraphQ: Scalable PIM-Based Graph Processing. 712-725 - Jaeyoung Jang, Jun Heo, Yejin Lee, Jaeyeon Won, Seonghak Kim, Sungjun Jung, Hakbeom Jang, Tae Jun Ham, Jae W. Lee:
Charon: Specialized Near-Memory Processing Architecture for Clearing Dead Objects in Memory. 726-739 - Youngeun Kwon, Yunjae Lee, Minsoo Rhu:
TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning. 740-753
Accelerators for Machine Learning 3
- Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna:
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach. 754-768 - Lillian Pentecost, Marco Donato, Brandon Reagen, Udit Gupta, Siming Ma, Gu-Yeon Wei, David Brooks:
MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation. 769-781 - Franyell Silfa, Gem Dot, José-María Arnau, Antonio González:
Neuron-Level Fuzzy Memoization in RNNs. 782-793 - Jacob R. Stevens, Ashish Ranjan, Dipankar Das, Bharat Kaul, Anand Raghunathan:
Manna: An Accelerator for Memory-Augmented Neural Networks. 794-806
Memory Systems & Storage
- Xiao Liu, David Roberts, Rachata Ausavarungnirun, Onur Mutlu, Jishen Zhao:
Binary Star: Coordinated Reliability in Heterogeneous Memory Systems for High Performance and Scalability. 807-820 - Gagandeep Panwar, Da Zhang, Yihan Pang, Mai Dahshan, Nathan DeBardeleben, Binoy Ravindran, Xun Jian:
Quantifying Memory Underutilization in HPC Systems and Using it to Improve Performance via Architecture Support. 821-835 - Yuanjiang Ni, Jishen Zhao, Heiner Litz, Daniel Bittman, Ethan L. Miller:
SSP: Eliminating Redundant Writes in Failure-Atomic NVRAMs via Shadow Sub-Paging. 836-848 - Renhai Chen, Zili Shao, Duo Liu, Zhiyong Feng, Tao Li:
Towards Efficient NVDIMM-based Heterogeneous Storage Hierarchy Management for Big Data Workloads. 849-860
Multicore/Parallel Architectures
- Lucas Morais, Vitor Silva, Alfredo Goldman, Carlos Álvarez, Jaume Bosch, Michael Frank, Guido Araujo:
Adding Tightly-Integrated Task Scheduling Acceleration to a RISC-V Multi-core Processor. 861-872 - Mayank Parasar, Natalie D. Enright Jerger, Paul V. Gratz, Joshua San Miguel, Tushar Krishna:
SWAP: Synchronized Weaving of Adjacent Packets for Network Deadlock Resolution. 873-885 - Diyu Zhou, Yuval Tamir:
PUSh: Data Race Detection Based on Hardware-Supported Prevention of Unintended Sharing. 886-898 - Daphne I. Gorman, Rafael Trapani Possignolo, Jose Renau:
EMI Architectural Model and Core Hopping. 899-910
Reconfigurable Architectures and FPGA
- Zhaoshi Li, Leibo Liu, Yangdong Deng, Jiawei Wang, Zhiwei Liu, Shouyi Yin, Shaojun Wei:
FPGA-Accelerated Optimistic Concurrency Control for Transactional Memory. 911-923 - Vidushi Dadu, Jian Weng, Sihao Liu, Tony Nowatzki:
Towards General Purpose Acceleration by Exploiting Common Data-Dependence Forms. 924-939 - Amirali Sharifian, Reza Hojabr, Navid Rahimi, Sihao Liu, Apala Guha, Tony Nowatzki, Arrvindh Shriraman:
μIR -An intermediate representation for transforming and optimizing the microarchitecture of application accelerators. 940-953
Security 3
- Jiyong Yu, Mengjia Yan, Artem Khyzha, Adam Morrison, Josep Torrellas, Christopher W. Fletcher:
Speculative Taint Tracking (STT): A Comprehensive Protection for Speculatively Accessed Data. 954-968 - Daniel Townley, Khaled N. Khasawneh, Dmitry Ponomarev, Nael B. Abu-Ghazaleh, Lei Yu:
LATCH: A Locality-Aware Taint CHecker. 969-982 - Nader Sehatbakhsh, Alireza Nazari, Haider Adnan Khan, Alenka G. Zajic, Milos Prvulovic:
EMMA: Hardware/Software Attestation Framework for Embedded Systems Using Electromagnetic Signals. 983-995
Caching & Virtualization
- Hao Wu, Krishnendra Nathella, Joseph Pusdesris, Dam Sunwoo, Akanksha Jain, Calvin Lin:
Temporal Prefetching Without the Off-Chip Metadata. 996-1008 - Anurag Mukkara, Nathan Beckmann, Daniel Sánchez:
PHI: Architectural Support for Synchronization- and Bandwidth-Efficient Commutative Scatter Updates. 1009-1022 - Artemiy Margaritov, Dmitrii Ustiugov, Edouard Bugnion, Boris Grot:
Prefetched Address Translation. 1023-1036
Measurement, Modeling, and Simulation
- Nikos Nikoleris, Lieven Eeckhout, Erik Hagersten, Trevor E. Carlson:
Directed Statistical Warming through Time Traveling. 1037-1049 - Donggyu Kim, Jerry Zhao, Jonathan Bachrach, Krste Asanovic:
Simmani: Runtime Power Modeling for Arbitrary RTL with Automatic Signal Selection. 1050-1062 - Mohammad Shahrad, Jonathan Balkind, David Wentzlaff:
Architectural Implications of Function-as-a-Service Computing. 1063-1075
Corrigendum
- Mengjia Yan, Jiho Choi, Dimitrios Skarlatos, Adam Morrison, Christopher W. Fletcher, Josep Torrellas:
InvisiSpec: Making Speculative Execution Invisible in the Cache Hierarchy (Corrigendum). 1076
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