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ORCIDIEEE Micro, Volume 39
Volume 39, Number 1, January - February 2019
- Lizy Kurian John:
To the Era of Intelligent Chips and Systems. 4-5 - Yuan Xie, Jishen Zhao:
Emerging Memory Technologies. 6-7 - Yeseong Kim, Mohsen Imani, Tajana Simunic Rosing:
Image Recognition Accelerator Design Using In-Memory Processing. 17-23 - Mimi Xie, Chen Pan, Youtao Zhang, Jingtong Hu, Yongpan Liu, Chun Jason Xue:
A Novel STT-RAM-Based Hybrid Cache for Intermittently Powered Processors in IoT Devices. 24-32 - Abhishek Kumar Jain
, G. Scott Lloyd, Maya B. Gokhale:
Performance Assessment of Emerging Memories Through FPGA Emulation. 8-16 - Nishil Talati, Heonjae Ha, Ben Perach, Ronny Ronen, Shahar Kvatinsky:
CONCEPT: A Column-Oriented Memory Controller for Efficient Memory and PIM Operations in RRAM. 33-43 - Pengfei Zuo, Yu Hua, Ming Zhao, Wen Zhou, Yuncheng Guo:
Write Deduplication and Hash Mode Encryption for Secure Nonvolatile Main Memory. 44-51 - Moinuddin K. Qureshi:
With New Memories Come New Challenges. 52-53 - Yiran Chen:
Reshaping Future Computing Systems With Emerging Nonvolatile Memory Technologies. 54-57 - Engin Ipek:
Memristive Accelerators for Dense and Sparse Linear Algebra: From Machine Learning to High-Performance Scientific Computing. 58-61 - Steven Swanson:
Redesigning File Systems for Nonvolatile Main Memory. 62-64 - Yan Solihin:
Persistent Memory: Abstractions, Abstractions, and Abstractions. 65-66 - Sam H. Noh:
Has the Time for EMT Finally Come? 67-68 - Shane Greenstein:
Six Infrastructure Trends. 70-72
Volume 39, Number 2, March - April 2019
- Lizy Kurian John:
Emerging Hot Chips and Systems. 4-5 - John Kubiatowicz, Stefan Rusu:
Hot Chips 30. 6-8 - Mark D. Hill, Jon Masters, Parthasarathy Ranganathan, Paul Turner, John L. Hennessy:
On the Spectre and Meltdown Processor Security Vulnerabilities. 9-19 - Doug Stiles:
The Hardware Security Behind Azure Sphere. 20-28 - Mohamed Arafa, Bahaa Fahim, Sailesh Kottapalli, Akhilesh Kumar, Lily Pao Looi, Sreenivas Mandava, Andy Rudoff, Ian M. Steiner, Bob Valentine, Geetha Vedaraman, Sujal Vora:
Cascade Lake: Next Generation Intel Xeon Scalable Processor. 29-36 - Jeff Rupley, Brad Burgess, Brian Grayson, Gerald D. Zuraski:
Samsung M3 Processor. 37-44 - Bill Gervasi:
Will Carbon Nanotube Memory Replace DRAM? 45-51 - Christopher Celio, Pi-Feng Chiu, Krste Asanovic, Borivoje Nikolic, David A. Patterson:
BROOM: An Open-Source Out-of-Order Processor With Resilient Low-Voltage Operation in 28-nm CMOS. 52-60 - Shane Greenstein:
Where the Frontier Thrives: Bricks, Mix, and Zip. 62-64
Volume 39, Number 3, May - June 2019
- Lizy Kurian John:
Top Picks. 4-5 - Sandhya Dwarkadas:
Top Picks in Computer Architecture from Conferences in 2018. 6-10 - Charles Eckert, Xiaowei Wang, Jingcheng Wang, Arun Subramaniyan, Dennis Sylvester, David T. Blaauw, Reetuparna Das, Ravi R. Iyer:
Neural Cache: Bit-Serial In-Cache Acceleration of Deep Neural Networks. 11-19 - Jeremy Fowers, Kalin Ovtcharov, Michael K. Papamichael, Todd Massengill, Ming Liu, Daniel Lo, Shlomi Alkalay, Michael Haselman, Logan Adams, Mahdi Ghandi, Stephen Heil, Prerak Patel, Adam Sapek, Gabriel Weisz, Lisa Woods, Sitaram Lanka, Steven K. Reinhardt, Adrian M. Caulfield, Eric S. Chung, Doug Burger:
Inside Project Brainwave's Cloud-Scale, Real-Time AI Processor. 20-28 - Yatish Turakhia, Gill Bejerano, William J. Dally:
Darwin: A Genomics Coprocessor. 29-37 - Martin Maas, Krste Asanovic, John Kubiatowicz:
A Hardware Accelerator for Tracing Garbage Collection. 38-46 - Sizhuo Zhang, Andrew Wright, Thomas Bourgeat:
Composable Building Blocks to Open Up Processor Design. 47-55 - Sagar Karandikar, Howard Mao, Donggyu Kim, David Biancolin, Alon Amid, Dayeol Lee, Nathan Pemberton, Emmanuel Amaro, Colin Schmidt, Aditya Chopra, Qijing Huang, Kyle Kovacs, Borivoje Nikolic, Randy Howard Katz, Jonathan Bachrach, Krste Asanovic:
FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud. 56-65 - Jo Van Bulck, Marina Minkin, Ofir Weisse, Daniel Genkin, Baris Kasikci, Frank Piessens, Mark Silberstein, Thomas F. Wenisch, Yuval Yarom, Raoul Strackx:
Breaking Virtual Memory Protection and the SGX Ecosystem with Foreshadow. 66-74 - Mohammadkazem Taram, Ashish Venkat, Dean M. Tullsen:
Context-Sensitive Decoding: On-Demand Microcode Customization for Security and Energy Management. 75-83 - Caroline Trippel, Daniel Lustig, Margaret Martonosi:
Security Verification via Automatic Hardware-Aware Exploit Synthesis: The CheckMate Approach. 84-93 - Aasheesh Kolli, Vaibhav Gogte, Ali G. Saidi, Stephan Diestelhorst, William Wang, Peter M. Chen, Satish Narayanasamy, Thomas F. Wenisch:
Language Support for Memory Persistency. 94-102 - Kate Nguyen, Kehan Lyu, Xianze Meng, Vilas Sridharan, Xun Jian:
Nonblocking DRAM Refresh. 103-109 - Aniruddh Ramrakhyani, Paul V. Gratz, Tushar Krishna:
Synchronized Progress in Interconnection Networks (SPIN): A New Theory for Deadlock Freedom. 110-117 - Shane Greenstein:
Misapplied Metaphors in AI Policy. 118-120
Volume 39, Number 4, July - August 2019
- Lizy Kurian John:
Secure Architectures. 4-5 - Simha Sethumadhavan, Mohit Tiwari:
Secure Architectures. 6-7 - Fan Yao, Hongyu Fang, Milos Doroslovacki, Guru Venkataramani:
Leveraging Cache Management Hardware for Practical Defense Against Cache Timing Channel Attacks. 8-16 - Rafael Misoczki, Sean Gulley, Vinodh Gopal, Martin G. Dixon, Hrvoje Vrsalovic, Wajdi K. Feghali:
Toward Postquantum Security for Embedded Cores. 17-26 - Pradip Bose, Saibal Mukhopadhyay:
Energy-Secure System Architectures (ESSA): A Workshop Report. 27-34 - Cynthia Sturton, Matthew Hicks, Samuel T. King, Jonathan M. Smith:
FinalFilter: Asserting Security Properties of a Processor at Runtime. 35-42 - Roman Kaplan, Leonid Yavits, Ran Ginosar:
RASSA: Resistive Prealignment Accelerator for Approximate DNA Long Read Mapping. 44-54 - Amirhossein Mirhosseini, Thomas F. Wenisch:
The Queuing-First Approach for Tail Management of Interactive Services. 55-64 - Shane Greenstein:
The Aftermath of the Dyn DDOS Attack. 66-68
Volume 39, Number 5, September - October 2019
- Lizy Kurian John:
Machine Learning Accelerators and More. 4-5 - Hadi Esmaeilzadeh, Jongse Park:
Machine Learning Acceleration. 6-7 - Thierry Moreau, Tianqi Chen, Luis Vega, Jared Roesch, Eddie Q. Yan, Lianmin Zheng, Josh Fromm, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
A Hardware-Software Blueprint for Flexible Deep Learning Specialization. 8-16 - Yongming Shen, Tianchu Ji, Michael Ferdman, Peter A. Milder:
Argus: An End-to-End Framework for Accelerating CNNs on FPGAs. 17-25 - Mostafa Mahmoud, Dylan Malone Stuart, Zissis Poulos, Alberto Delmas Lascorz, Patrick Judd, Sayeh Sharify, Milos Nikolic, Kevin Siu, Isak Edo Vivancos, Jorge Albericio, Andreas Moshovos:
Accelerating Image-Sensor-Based Deep Learning Applications. 26-35 - Marc Riera, José-María Arnau, Antonio González:
CGPA: Coarse-Grained Pruning of Activations for Energy-Efficient RNN Inference. 36-45 - Bahar Asgari, Ramyad Hadidi, Hyesoon Kim, Sudhakar Yalamanchili:
ERIDANUS: Efficiently Running Inference of DNNs Using Systolic Arrays. 46-54 - Ahmet Caner Yuzuguler, Firat Celik, Mario Drumond, Babak Falsafi, Pascal Frossard:
Analog Neural Networks With Deep-Submicrometer Nonlinear Synapses. 55-63 - Mingu Kang, Prakalp Srivastava, Vikram S. Adve, Nam Sung Kim, Naresh R. Shanbhag:
An Energy-Efficient Programmable Mixed-Signal Accelerator for Machine Learning Algorithms. 64-72 - Jonghyun Bae, Hakbeom Jang, Jeonghun Gong, Wenjing Jin, Shine Kim, Jaeyoung Jang, Tae Jun Ham, Jinkyu Jeong, Jae W. Lee:
SSDStreamer: Specializing I/O Stack for Large-Scale Machine Learning. 73-81 - Youngeun Kwon, Minsoo Rhu:
A Disaggregated Memory System for Deep Learning. 82-90 - Saptadeep Pal, Eiman Ebrahimi, Arslan Zulfiqar, Yaosheng Fu, Victor Zhang, Szymon Migacz, David W. Nellans, Puneet Gupta:
Optimizing Multi-GPU Parallelization Strategies for Deep Learning Training. 91-101 - Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Wei Wang, Jintao Zhang, Marcel Schaal, Mauricio J. Serrano, Kazuaki Ishizaki, Hiroshi Inoue, Eri Ogawa, Moriyoshi Ohara, Leland Chang, Kailash Gopalakrishnan:
DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator. 102-111 - Richard Mateosian:
What I Missed. 114-116 - Mark D. Hill:
Reflections and Research Advice Upon Receiving the 2019 Eckert-Mauchly Award. 119-124 - Shane Greenstein:
Earning Stripes in Medical Machine Learning. 126-128
Volume 39, Number 6, November - December 2019
- Lizy Kurian John:
3-D Chips! Chips are Getting Denser and Taller Than Ever!! 4-5 - Vijaykrishnan Narayanan:
Going Vertical: The Future of Electronics. 6-7 - Suman Datta, Sourav Dutta, Benjamin Grisafe, Jeff Smith, Srivatsa Srinivasa, Huacheng Ye:
Back-End-of-Line Compatible Transistors for Monolithic 3-D Integration. 8-15 - Mindy D. Bishop, H.-S. Philip Wong, Subhasish Mitra, Max M. Shulaker:
Monolithic 3-D Integration. 16-27 - Zhixiao Zhang, Xin Si, Srivatsa Srinivasa, Akshay Krishna Ramanathan, Meng-Fan Chang:
Recent Advances in Compute-in-Memory Support for SRAM Using Monolithic 3-D Integration. 28-37 - Sai Pentapati, Lingjun Zhu, Lennart Bamberg, Da Eun Shim, Alberto García Ortiz, Sung Kyu Lim:
A Logic-on-Memory Processor-System Design With Monolithic 3-D Technology. 38-45 - Itir Akgun, Dylan C. Stow, Yuan Xie:
Network-on-Chip Design Guidelines for Monolithic 3-D Integration. 46-53 - Shihui Yin, Jae-sun Seo, Yulhwa Kim, Xu Han, Hugh J. Barnaby, Shimeng Yu, Yandong Luo, Wangxin He, Xiaoyu Sun, Jae-Joon Kim:
Monolithically Integrated RRAM- and CMOS-Based In-Memory Computing Optimizations for Efficient Deep Learning. 54-63 - Meenatchi Jagasivamani, Candace Walden, Devesh Singh, Luyi Kang, Shang Li, Mehdi Asnaashari, Sylvain Dubois, Bruce L. Jacob, Donald Yeung:
Analyzing the Monolithic Integration of a ReRAM-Based Main Memory Into a CPU's Die. 64-72 - Marco Donato, Lillian Pentecost, David Brooks, Gu-Yeon Wei:
MEMTI: Optimizing On-Chip Nonvolatile Storage for Visual Multitask Inference at the Edge. 73-81 - Shane Greenstein:
Antitrust in Three Acts. 82-84
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