Greetings Jim, Welcome to the IAP Newsletter with recent and upcoming research publications, news and events. Research includes applications and infrastructure for AI and machine learning, security, hardware acceleration, networking, and storage.

SAVE the DATE: CMU WORKSHOP on the FUTURE of AI and SECURITY in the CLOUD 

Date: Friday November 8, 2024 - 8:30am-4:00pm EDT

Venue: Gates Hillman Complex, Room 6115, CMU, Pittsburgh, PA 

In collaboration with CyLab, expect a full day of talks by leading experts in academia and industry working in AI and machine learning, security, hardware acceleration, networking, and storage.

This workshop is co-organized by the IAP and Prof. Riccardo Paccagnella (above), in collaboration with CyLab.

UCI WORKSHOP ON THE FUTURE OF AI and CLOUD COMPUTING 

Thursday May 2, 2024 @ UC Irvine, Irvine, CA

Prof. Jason Cong, UCLA, Volgenau Chair for Engineering Excellence, opens the morning session.

Speakers on May 2 (by order of appearance): 

Prof. Jason Cong, UCLA, Volgenau Chair for Engineering Excellence, "Can We Automate Chip Design with Deep Learning?" 

Prof. Hyoukjun Kwon, UCI, "ML Workloads in AR/VR and their Implication to the ML System Design"

Prof. Quanquan Gu, UCLA and Head of AIDD at ByteDance, "Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models"

Dr. Ian Colbert, AMD, "Quantizing Neural Networks for Efficient AI Inference"

Dr. Somdeb Majumdar, Director of Intel AI Lab, "The Era of Foundation Models – What Lies Beyond LLMs"

Prof. Miryung Kim, UCLA, Vice Chair of Graduate Studies and Amazon Scholar at AWS, "Software Engineering for Data Intensive Scalable Computing and Heterogeneous Computing"

Prof. Aparna Chandramowlishwaran, UCI, "Domain Decomposition meets Neural Operator: AI4Science at Scale"

Dr. Ramyad Hadidi, Rain AI, "On-Device Computing: Rain AI’s Mission for Energy-Efficient AI Hardware"

Prof. Nikil Dutt, UCI, Chancellor's Professor of Computer Science, "Adaptive Computer Systems through Computational Self-Awareness"

This was the first AI and Cloud Workshop hosted by UCI. Please see the UCI WORKSHOP WEB PAGE for the speaker bios, abstracts and videos of the presentations.

SELECT CONFERENCES and PUBLICATIONS in 1H 2024

POPL 2024, The 51st ACM Symposium on Principles of Programming Languages, January 14-20, 2024, London, UK

The Network is the Computer: A Programming Language Perspective

Nate Foster, Cornell University and Jane Street

Inside the Scala Capture Checker

Martin Odersky, EPFL

Computational-Bounded Robust Compilation and Universally Composable Security

Robert Künnemann, CISPA Helmholtz Center for Information Security, Ethan Cecchetti, University of Wisconsin-Madison

FAST '24 - The 22nd USENIX Conference on File and Storage Technologies - February 26-29, 2024, Santa Clara, CA, USA

Baleen: ML Admission & Prefetching for Flash Caches Prefetching for Flash Caches

Daniel Lin-Kit Wong, Carnegie Mellon University; Hao Wu, Meta; Carson Molder, UT Austin; Sathya Gunasekar, Jimmy Lu, Snehal Khandkar, and Abhinav Sharma, Meta; Daniel S. Berger, Microsoft and University of Washington; Nathan Beckmann and Gregory R. Ganger, Carnegie Mellon University

What's the Story in EBS Glory: Evolutions and Lessons in Building Cloud Block Store

Weidong Zhang, Erci Xu, Qiuping Wang, Xiaolu Zhang, Yuesheng Gu, Zhenwei Lu, Tao Ouyang, Guanqun Dai, Wenwen Peng, Zhe Xu, Shuo Zhang, Dong Wu, Yilei Peng, Tianyun Wang, Haoran Zhang, Jiasheng Wang, Wenyuan Yan, Yuanyuan Dong, Wenhui Yao, Zhongjie Wu, Lingjun Zhu, Chao Shi, Yinhu Wang, Rong Liu, Junping Wu, Jiaji Zhu, and Jiesheng Wu, Alibaba Group

Awarded Best Paper!

HPCA 2024 - The 30th IEEE International Symposium on High-Performance Computer Architecture - March 2-6, 2024, Edinburgh, Scotland

Keynote: Terminus: Moving the Center of Cloud Servers to SmartNICs and Beyond, Derek Chiou

Revet: A Language and Compiler for Dataflow Threads

Alexander Rucker, Shiv Sundram, Coleman Smith, Matt Vilim, Raghu Prabhakar, Fredrik Kjolstad, Kunle Olukotun

MIMDRAM: An End-to-End Processing-Using-DRAM System for High-Throughput, Energy-Efficient and Programmer-Transparent Multiple-Instruction Multiple-Data Computing 

Geraldo Francisco De Oliveira Junior, Ataberk Olgun, Giray Yaglikci, Nisa Bostanci, Juan Gómez Luna, Saugata Ghose, Onur Mutlu

CAMEL: Co-Designing AI Models and eDRAMs for Efficient On-Device Learning

Sai Qian Zhang, Thierry Tambe, Nestor Cuevas, Gu-Yeon Wei, David Brooks

LibPreemptible: Enabling Fast, Adaptive, and Hardware-Assisted User-Space Scheduling

Yueying Li, Nikita Lazarev, David Koufaty, Yijun Yin, Andy Anderson, Zhiru Zhang, G. Edward Suh, Kostis Kaffes, Christina Delimitrou, David Koufaty

Data Motion Acceleration: Chaining Cross-Domain Multi Accelerators

Shu-Ting Wang, Hanyang Xu, Amin Mamandipoor, Rohan Mahapatra, Byung Hoon Ahn, Soroush Ghodrati, Krishnan Kailas, Mohammad Alian, Hadi Esmaeilzadeh

ASPLOS 2024 - The 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, April 27-May 1, 2024, San Diego, CA

Keynote: Societal infrastructure in the age of Artificial General Intelligence,

Amin Vahdat

CC-NIC: a Cache-Coherent Interface to the NIC

Henry N. Schuh and Arvind Krishnamurthy (Google and University of Washington); David Culler (Google); Henry M. Levy (Google and University of Washington); Luigi Rizzo (Google); Samira Khan (Google and University of Virginia); Brent E. Stephens (Google and University of Utah)

DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads

Seah Kim (University of California Berkeley); Hyoukjun Kwon (University of California Irvine); Jinook Song, Jihyuck Jo, Yu-Hsin Chen, Liangzhen Lai, and Vikas Chandra (Meta)

8-bit Transformer Inference and Fine-tuning for Edge Accelerators

Jeffrey Yu, Kartik Prabhu, Yonatan Urman, Robert M. Radway, Eric Han, and Priyanka Raina (Stanford University)

Keynote: Challenges and Opportunities for Systems Using CXL Memory, Emmett Witchel

BaCO: A Fast and Portable Bayesian Compiler Optimization Framework

Erik Orm Hellsten (Lund University);Artur Souza (Federal University of Minas Gerais); Johannes Lenfers (University of Münster); Rubens Lacouture and Olivia Hsu (Stanford University);Adel Ejjeh (University of Illinois at Urbana-Champaign); Fredrik Kjolstad (Stanford University); Michel Steuwer (University of Edinburgh); Kunle Olukotun (Stanford University); Luigi Nardi (Lund University and Stanford University)

Characterizing a Memory Allocator at Warehouse Scale

Zhuangzhuang Zhou (Cornell University); Vaibhav Gogte, Nilay Vaish, Chris Kennelly, Patrick Xia, Svilen Kanev, and Tipp Moseley (Google); Christina Delimitrou (MIT); Parthasarathy Ranganathan (Google)

Tandem Processor: Grappling with Emerging Operators in Neural Networks

Soroush Ghodrati, Sean Kinzer, Hanyang Xu, and Rohan Mahapatra (University of California San Diego); Yoonsung Kim (KAIST); Byung Hoon Ahn (University of California San Diego); Dong Kai Wang (University of Illinois Urbana-Champaign); Lavanya Karthikeyan (University of California San Diego); Amir Yazdanbakhsh (Google DeepMind); Jongse Park (KAIST); Nam Sung Kim (University of Illinois Urbana-Champaign); Hadi Esmaeilzadeh (University of California San Diego)

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

Maximilian Lam (Harvard University); Jeff Johnson (Meta); Wenjie Xiong (Virginia Tech); Kiwan Maeng (Pennsylvania State University); Udit Gupta (Harvard University); Yang Li, Liangzhen Lai, and Ilias Leontiadis (Meta); Minsoo Rhu (KAIST and Meta); Hsien-Hsin S. Lee (Intel); Vijay Janapa Reddi, Gu-Yeon Wei, and David Brooks (Harvard University); Edward Suh (Meta and Cornell University)

RPG^2: Robust Profile-Guided Runtime Prefetch Generation

Yuxuan Zhang, Nathan Sobotka, and Soyoon Park (University of Pennsylvania);Saba Jamilan (University of California Santa Cruz);Tanvir Ahmed Khan (Columbia University);Baris Kasikci (University of Washington and Google);Gilles A Pokam (Intel);Heiner Litz (University of California Santa Cruz);Joseph Devietti (University of Pennsylvania)

NSDI '24 - The 21st USENIX Symposium on Networked Systems Design and Implementation - April 16-18, 2024, Santa Clara, CA

Can't Be Late: Optimizing Spot Instance Savings under Deadlines

Zhanghao Wu, Wei-Lin Chiang, Ziming Mao, and Zongheng Yang, University of California, Berkeley; Eric Friedman and Scott Shenker, University of California, Berkeley, and ICSI; Ion Stoica, University of California, Berkeley

Awarded Outstanding Paper!

Sieve is Simpler than LRU: An Efficient Turn-Key Eviction Algorithm for Web Caches

Yazhuo Zhang, Juncheng Yang, Yao Yue, Ymir Vigfusson, K. V. Rashmi

Community Award Winner!

Sidekick: In-Network Assistance for Secure End-to-End Transport Protocols

Gina Yuan, Matthew Sotoudeh, and David K. Zhang, Stanford University; Michael Welzl, University of Oslo; David Mazières and Keith Winstein, Stanford University

Outstanding Paper Award and Community Award Winner!

TECC: Towards Efficient QUIC Tunneling via Collaborative Transmission Control

Jiaxing Zhang, Alibaba Group, University of Chinese Academy of Sciences; Furong Yang, Alibaba Group; Ting Liu, Alibaba Group, University of Chinese Academy of Sciences; Qinghua Wu, University of Chinese Academy of Sciences, Purple Mountain Laboratories, China; Wu Zhao, Yuanbo Zhang, Wentao Chen, Yanmei Liu, Hongyu Guo, and Yunfei Ma, Alibaba Group; Zhenyu Li, University of Chinese Academy of Sciences, Purple Mountain Laboratories, China

BBQ: A Fast and Scalable Integer Priority Queue for Hardware Packet Scheduling

Nirav Atre, Hugo Sadok, and Justine Sherry, Carnegie Mellon University

Sirius: Composing Network Function Chains into P4-Capable Edge Gateways

Jiaqi Gao, Jiamin Cao, Yifan Li, Mengqi Liu, Ming Tang, Dennis Cai, and Ennan Zhai, Alibaba Cloud

CASSINI: Network-Aware Job Scheduling in Machine Learning Clusters

Sudarsanan Rajasekaran and Manya Ghobadi, Massachusetts Institute of Technology; Aditya Akella, UT Austin

ExChain: Exception Dependency Analysis for Root Cause Diagnosis

Ao Li, Carnegie Mellon University; Shan Lu, Microsoft Research and University of Chicago; Suman Nath, Microsoft Research; Rohan Padhye and Vyas Sekar, Carnegie Mellon University

EuroSys 2024 - April 22-25, 2024, Athens, Greece

Model Selection for Latency-Critical Inference Serving

Daniel Mendoza (Stanford University), Francisco Romero (Stanford University), Caroline Trippel (Stanford University)

Enoki: High Velocity Linux Kernel Scheduler Development

Samantha Miller (University of Washington), Anirudh Kumar (University of Washington), Tanay Vakharia (University of Washington), Ang Chen (University of Michigan), Danyang Zhuo (Duke University), Thomas Anderson (University of Washington)

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Foteini Strati (ETH Zurich), Xianzhe Ma (ETH Zurich), Ana Klimovic (ETH Zurich)

ZKML: An Optimizing System for ML Inference in Zero-Knowledge Proofs

Bing-Jyue Chen (UIUC), Suppakit Waiwitlikhit (Stanford), Ion Stoica (UC Berkeley), Daniel Kang (UIUC)

ISCA 51 - The International Symposium on Computer Architecture 

June 29-July 3, 2024, Buenos Aires, Argentina

Constable: Improving Performance and Power Efficiency by Safely Eliminating Load Execution

R. Bera, A. Ranganathan, J. Rakshit, S. Mahto, A. Nori, J. Gaur, A. Olgun, K. Kanellopoulos, M. Sadrosadati, S. Subramoney, O. Mutlu

FireAxe: Partitoned FPGA-Accelerated Simulation of Large-Scale RTL Designs

J. Whangbo, E. Lim, C. Zhang, K. Anderson, A. Gonzalez, R. Gupta, N. Krishnakumar, S. Karandikar, B. Nikolic, Y. Shao, K. Asanovic

MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems

S. Hsia, A. Golden, B. Acun, N. Ardalani, Z. DeVito, G. Wei, D. Brooks, C. Wu

Trapezoid: A Versatile Accelerator for Dense and Sparse Matrix Multiplications 

Y. Yang, J. Emer, D. Sanchez

UDP: Utility-Driven Fetch Directed Instruction Prefetching 

S. Oh, M. Xu, T. Khan, B. Kasikci, H. Litz

BLOGS

AI on Trial: Legal Models Hallucinate in 1 out of 6 (or More) Benchmarking Queries. A new study reveals the need for benchmarking and public evaluations of AI tools in law.

Varun Magesh, Faiz Surani, Matthew Dahl, Mirac Suzgun, Christopher D. Manning, Daniel E. Ho (HAI Blog)

May 23, 2024

Avalanche Consensus - Does it Perform as Promised?

Philipp Schneider, Ignacio Amores-Sesar, and Christian Cachin (University of Bern) (IC3 Blog)

May 17, 2024

The Shift from Models to Compound AI Systems

Matei Zaharia, Omar Khattab, Lingjiao Chen, Jared Quincy Davis, Heather Miller, Chris Potts, James Zou, Michael Carbin, Jonathan Frankle, Naveen Rao, Ali Ghodsi (BAIR Blog)

Feb 18, 2024

AWARDS and TRANSITIONS for IAP COLLEAGUES

American Academy of Arts and Sciences - New Academy Members 2024

Jason Cong, UCLA

2024 Sloan Fellows

Nathan Beckmann, Carnegie Mellon University

Priyanka Raina, Stanford University

Yakun Sophia Shao, University of California, Berkeley

Justine Sherry, Carnegie Mellon University

2023 ACM Fellows (announced in January 2024)

Aditya Akella, UT Austin

Emmett Witchel, UT Austin

2023 Intel Outstanding Researcher Award (announced in January 2024)

Caroline Trippel, Stanford

NSF EXPEDITIONS in COMPUTING AWARDS

Carbon Connect -- An Ecosystem for Sustainable Computing

AWARD: $12M

Co-led by IAP Advisor David Brooks, Harvard and Benjamin Lee, Penn

Learning Directed Operating System -- A Clean-Slate Paradigm for Operating Systems Design and Implementation

AWARD: $12M

Aditya Akella and Chris Rossbach, UT Austin, Michael Swift, Wisconsin,

Philip Godfrey, UIUC, Sebastian Angel, Penn

BEST PAPER AWARDS

IEEE MICRO TOP PICKS 2024

RowPress: Amplifying Read Disturbance in Modern DRAM Chips

Haocong Luo, Ataberk Olgun, A. Giray Yağlıkçı, Yahya Can Tuğrul, Steve Rhyner Meryem Banu Cavlak, Joël Lindegger, Mohammad Sadrosadati, Onur Mutlu

Ditto: End-to-End Application Cloning for Networked Cloud Services

Mingyu Liang, Yu Gan, Yueying Li (Cornell Univ.); Carlos Torres, Abhishek Dhanotia (Meta); Mahesh Ketkar (Intel); Christina Delimitrou (Massachusetts Inst. of Technology)

ASPLOS 2024 INFLUENTIAL PAPER AWARD



2013: Paragon: QoS-Aware Scheduling for Heterogeneous Datacenters

Christina Delimitrou and Christos Kozyrakis

NSDI ’24 BEST PAPER AWARDS (see NSDI ’24 Summary above)

FACULTY CHAIRS

Heiner Litz was appointed the Kumar Malavalli Endowed Chair in Storage Systems at UCSC.

PROJECTS

PROJECTS in ML SYSTEMS

ML Systems with Tiny ML

An update is imminent of this community-driven project, with content generated collaboratively by numerous contributors over time. The content creation process may have involved various editing tools, including generative AI technology. As the main author, editor, and curator, Prof. Vijay Janapa Reddi maintains human oversight and editorial control to ensure the accuracy and relevance of the content. Have you got questions or feedback? Feel free to e-mail Prof. Vijay Janapa Reddi directly, or you are welcome to start a discussion thread on GitHub.



PROJECTS in DATA CENTER NETWORKING

CC-NIC: a Cache-Coherent Interface to the NIC

Henry N. Schuh and Arvind Krishnamurthy (Google and University of Washington); David Culler (Google); Henry M. Levy (Google and University of Washington); Luigi Rizzo (Google); Samira Khan (Google and University of Virginia); Brent E. Stephens (Google and University of Utah)

NEWS ITEMS

June 3, 2024

Computex 2024: The Battle for AI Copilot PCs Begins

May 23, 2024

Sustainable computing project awarded $12 million from NSF

April 24, 2024

US investigates China's access to RISC-V — open standard instruction set may become new site of US-China chip war

March 28, 2024

Amazon Bets $150 Billion on Data Centers Required for AI Boom

February 20, 2024

Google Announces Free AI Cyber Tools to Bolster Online Security

December 6, 2023

AMD Takes On Nvidia with New GPU for AI

IAP Workshop Testimonials

Professor David Patterson, the Pardee Professor of Computer Science, UC Berkeley, “I saw strong participation at the Cloud Workshop, with some high energy and enthusiasm; and I was delighted to see industry engineers bring and describe actual hardware, representing some of the newest innovations in the data center.”

Professor Christos Kozyrakis, Professor of Electrical Engineering & Computer Science, Stanford University, “As a starting point, I think of these IAP workshops as ‘Hot Chips meets ISCA’, i.e., an intersection of industry’s newest solutions in hardware (Hot Chips) with academic research in computer architecture (ISCA); but more so, these workshops additionally cover new subsystems and applications, and in a smaller venue where it is easy to discuss ideas and cross-cutting approaches with colleagues.”

​

Professor Hakim Weatherspoon, Professor of Computer Science, Cornell University, “I have participated in three IAP Workshops since the first one at Cornell in 2013 and it is great to see that the IAP premise was a success now as it was then, bringing together industry and academia in a focused workshop and an all-day exchange of ideas. It was a fantastic experience and I look forward to the next IAP Workshop.” 

Professor Ken Birman, the N. Rama Rao Professor of Computer Science, Cornell University, “I actually thought it was a fantastic workshop, an unquestionable success, starting from the dinner the night before, through the workshop itself, to the post-event reception for the student Best Poster Awards.” 

Dr. Carole-Jean Wu, Research Scientist, AI Infrastructure, Facebook Research, and Professor of CSE, Arizona State University, “The IAP Cloud Computing workshop provides a great channel for valuable interactions between faculty/students and the industry participants. I truly enjoyed the venue learning about research problems and solutions that are of great interest to Facebook, as well as the new enabling technologies from the industry representatives. The smaller venue and the poster session fostered an interactive environment for in-depth discussions on the proposed research and approaches and sparked new collaborative opportunities. Thank you for organizing this wonderful event! It was very well run.” 

Nathan Pemberton, PhD student, UC Berkeley (currently Applied Scientist at AWS), "IAP workshops provide a valuable chance to explore emerging research topics with a focused group of participants, and without all the time/effort of a full-scale conference. Instead of rushing from talk to talk, you can slow down and dive deep into a few topics with experts in the field."  

Dr. Pankaj Mehra, VP Product Planning, Samsung (currently CEO Elephance Memory),  "Terrifically organized Workshops that give all parties -- students, faculty, industry -- valuable insights to take back"

Professor Vishal Shrivastav, Purdue University, “Attending the IAP workshops as a PhD student at Cornell was a great experience and very rewarding. I really enjoyed the many amazing talks from both the industry and academia. My personal conversations with several industry leaders at the workshop will definitely guide some of my future research." 

Professor Ana Klimovic, ETH Zurich, “I attended three IAP workshops as a PhD student at Stanford, and I am consistently impressed by the quality of the talks and the breadth of the topics covered. These workshops bring top-tier industry and academia together to discuss cutting-edge research challenges. It is a great opportunity to exchange ideas and get inspiration for new research opportunities." ​

​Dr. Richard New, VP Research, Western Digital, “IAP workshops provide a great opportunity to meet with professors and students working at the cutting edge of their fields. It was a pleasure to attend the event – lots of very interesting presentations and posters.” 

Support a unique tech forum that brings together academia and industry under your company's banner? 

Please feel free to contact us regarding sponsorship opportunities, and for more info about any of the items above.

Best,

Jim Ballingall

Executive Director

Industry-Academia Partnership (IAP) 

www.industry-academia.org

jim.ballingall@gmail.com

cel: 408-212-1035

Copyright © 2013-2024 Industry-Academia Partnership