CACM Research Highlights NominationsThe SIGARCH executive committee established a sub-committee in 2013 to nominate papers from SIGARCH sponsored conferences for CACM Research Highlights.
The committee requests the program chair of each SIGARCH conference to recommend up to three papers for consideration. The recommendations should be made after the conference completes, to take into account community reaction, but no more than one week after the last day.
It is important to note that the criteria for nominations to Research Highlights are not necessarily the same as those for traditional conference best paper awards. The nominations need to be of broad interest beyond the architecture community. They must create excitement and do not necessarily need to have all the details worked out. Papers with surprising results that stir stimulating debate at the conference are particularly encouraged.
The committee encourages program chairs to run an audience survey as input for their recommendations. An example survey used in a recent conference appears at https://www.surveymonkey.com/s/M35DH7T.
Program chairs should send their recommendations to the SIGARCH vice-chair at firstname.lastname@example.org along with the process used. The final selection by the CACM board is competitive. To aid in writing strong nominations, the committee requests program chairs to forward reviews and author responses for the nominated papers. These have been very helpful in the past; e.g., to highlight strengths, address any perceived weaknesses, and identify technical perspective writers. Please see the SIGARCH policy below regarding this issue.
SIGARCH permits PC chairs of SIGARCH sponsored conferences to forward review materials (including reviews, online discussion comments among reviewers, and author responses) to the SIGARCH committee for nominating papers for CACM research highlights, subject to the following requirements:
(1) A committee member with a conflict of interest for a paper will not see the review materials for the paper.
(2) The PC chair will obtain permission from the authors before forwarding the review materials for a paper to the committee.
(3) The PC chair will either redact reviewer identifying information from the review materials forwarded to the committee or will obtain permission from the reviewers to provide this information.
To simplify (2), SIGARCH encourages PC chairs to include the following statement in the call for papers:
According to SIGARCH guidelines, reviewer comments and author rebuttals for selected papers may be shared with (non-conflicted) members of the SIGARCH committee for nominating papers for CACM research highlights.
To simplify (3), SIGARCH encourages PC chairs to include the following statement in the invitation to PC members, ERC members, and ad hoc reviewers:
According to SIGARCH guidelines, reviews and online discussion comments for selected papers (along with reviewer identification) may be shared with (non-conflicted) members of the SIGARCH committee for nominating papers for CACM research highlights.
University of Toronto
Vijayalakshmi (Viji) Srinivasan
Architecting Noisy Intermediate-Scale Trapped Ion Quantum Computers.
Prakash Murali, Dripto M. Debroy, Kenneth R. Brown, Margaret Martonosi
Orbital Edge Computing: Nanosatellite Constellations as a New Class of Computer System.
Bradley Denby, Brandon Lucia
Boosted Race Trees for Low Energy Classification.
Georgios Tzimpragos, Advait Madhavan, Dilip Vasudevan, Dmitri Strukov, Timothy Sherwood
Cryogenic Computer Architecture Modeling with Memory-Side Case Studies.
Gyu-hyeon Lee, Dongmoon Min, Ilkwon Byun, Jangwoo Kim
Darwin: A Genomics Co-processor Provides up to 15,000X Acceleration on Long Read Assembly.
Yatish Turakhia, Gill Bejerano, William J. Dally.
Firesim: FPGA-accelerated Cycle-exact Scale-out System Simulation in the Public Cloud.
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 Katz, Jonathan Bachrach, Krste Asanović.
Bolt: I Know What You Did Last Summer… In the Cloud.
Christina Delimitrou, Christos Kozyrakis.
In-Datacenter Performance Analysis of a Tensor Processing Unit.
Norman P. Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, C. Richard Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross, Matt Ross, Amir Salek, Emad Samadiani, Chris Severn, Gregory Sizikov, Matthew Snelham, Jed Souter, Dan Steinberg, Andy Swing, Mercedes Tan, Gregory Thorson, Bo Tian, Horia Toma, Erick Tuttle, Vijay Vasudevan, Richard Walter, Walter Wang, Eric Wilcox, Doe Hyun Yoon.
The Computational Sprinting Game.
Songchun Fan, Seyed Majid Zahedi, Benjamin C. Lee.
OpenPiton: An Open Source Manycore Research Framework.
Jonathan Balkind, Michael McKeown, Yaosheng Fu, Tri Nguyen, Yanqi Zhou, Alexey Lavrov, Mohammad Shahrad, Adi Fuchs, Samuel Payne, Xiaohua Liang, Matthew Matl, David Wentzlaff.
ASIC clouds: Specializing the Datacenter.
Ikuo Magaki, Moein Khazraee, Luis Vega Gutierrez, Michael Bedford Taylor.
Profiling a Warehouse-scale Computer.
Svilen Kanev, Juan Pablo Darago, Kim Hazelwood, Parthasarathy Ranganathan, Tipp Moseley, Gu-Yeon Wei, David Brooks.
Exploring the potential of heterogeneous von neumann/dataflow execution models.
Tony Nowatzki, Vinay Gangadhar, Karthikeyan Sankaralingam.
DianNao: A Small-Footprint High-Throughput Accelerator for Ubiquitous Machine-Learning.
Tianshi Chen, Zidong Du, Jia Wang, Ninghui Sun, Jia Wang, Chengyong Wu, Yunji Chen, Olivier Temam.
A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services.
Andrew Putnam, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinidesy, John Demmez, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger.
HELIX-RC: An Architecture-Compiler Co-Design for Automatic Parallelization of Irregular Programs.
Simone Campanoni, Kevin Brownell, Svilen Kanev, Timothy M. Jones, Gu-Yeon Wei, David Brooks.
Convolution Engine: Balancing Efficiency & Flexibility in Specialized Computing.
Wajahat Qadeer, Rehan Hameed, Ofer Shacham, Preethi Venkatesan, Christos Kozyrakis, Mark A. Horowitz.
Can traditional programming bridge the Ninja performance gap for parallel computing applications?
Nadathur Satish, Changkyu Kim, Jatin Chhugani, Hideki Saito, Rakesh Krishnaiyer, Mikhail Smelyanskiy, Milind Girkar, Pradeep Dubey.