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Greetings Jim, Welcome to the IAP Newsletter with research publications, conferences and news regarding applications and infrastructure for AI and machine learning, hardware acceleration, operating systems, networking, security, and storage.
In this edition, we highlight key papers at ISPASS, MLSys, ISCA, USENIX ATC, SIGCOMM, SPLASH, MICRO-57, SoCC and NeurIPS, in addition to Awards, Books, Blogs and News Items. We begin with a recap of recent IAP Workshops at Carnegie Mellon and the University of California.
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AI and CLOUD WORKSHOPS - 2024 | |
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CMU professors Giulia Fanti, Wenting Zheng and Fei Fang present their research on November 8.
Speakers included (in order of appearance):
Prof. Lujo Bauer, CMU, “From Pandas and Gibbons to Malware Detection: Attacking and Defending Real-world Uses of Machine Learning”
Prof. Fei Fang, CMU, “Game Theory and Machine Learning for Addressing Societal Challenges: From Theory to Real-World Impact”
Dr. Daniel Kroening, Amazon Web Services, “The Role of Compilers in Accelerating GenAI”
Prof. Riccardo Paccagnella, CMU, “Timing Attacks on Constant-Time Code"
Prof. Vyas Sekar, CMU, “Enabling Data-driven Innovation with Synthetic Data”
Prof. Wenting Zheng, CMU and Opaque Systems, "Cryptographic Systems for Private and Secure Generative AI"
Prof. Giulia Fanti, CMU, “Gen-T: Reducing the Triage Cost of Distributed Tracing Using Generative Models”
Dr. Andrew Schmidt, AMD, “Leveraging Ryzen AI’s Neural Processing Units in the Heterogenous Computing Landscape”
This was the third AI and Cloud Workshop hosted by CMU. Please see the CMU WORKSHOP WEB PAGE for the speaker bios, abstracts and videos of the presentations.
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UCI WORKSHOP ON THE FUTURE OF AI AND CLOUD COMPUTING
Thursday, May 2, 2024
Interdisciplinary Science & Engineering Building, UC Irvine, Irvine, CA
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Prof. Jason Cong, UCLA, Volgenau Chair for Engineering Excellence, opens the morning session,"Can We Automate Chip Design with Deep Learning?"
Other Speakers on May 2 included:
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.
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COMING in SPRING 2025
UW AI and CLOUD WORKSHOP
University of Washington
Seattle, WA
Please watch for IAP Newsletters and our website for further updates on the date and agenda.
In the photo below, Avinash Sodani and Doug Burger catch up during a break at a previous IAP Workshop at UW.
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SELECT CONFERENCES and PUBLICATIONS in MAY-DECEMBER 2024
ISPASS 2024 - IEEE International Symposium on Performance Analysis of Systems and Software, Indianapolis, IN, May 5-7, 2024
Tanner Andrulis, Vivienne Sze, Joel S. Emer (MIT)
BEST PAPER AWARD!
Vision Transformer Computation and Resilience for Dynamic Inference
Kavya Sreedhar (Stanford University), Jason Clemons (NVIDIA), Rangharajan Venkatesan (NVIDIA), Stephen W. Keckler (NVIDIA), Mark Horowitz (Stanford University)
SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems
Kailash gogineni (George Washington University), Sai Santosh Dayapule (George Washington University), Juan Gomez-Luna (ETH Zurich), Karthikeya Gogineni (Unaffiliated), Peng Wei (George Washington University), Tian Lan (George Washington University), Mohammad Sadrosadati (ETH Zurich), Onur Mutlu (ETH Zurich and Stanford), Guru Venkataramani (George Washington University)
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation
Alicia Golden (Harvard University), Samuel Hsia (Harvard University), Fei Sun (Meta), Bilge Acun (FAIR Meta), Basil Hosmer (FAIR Meta), Yejin Lee (FAIR Meta), Zachary DeVito (FAIR Meta), Jeff Johnson (FAIR Meta), Gu-Yeon Wei (Harvard University), David Brooks (Harvard University), Carole-Jean Wu (FAIR Meta)
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MLSys 2024, Santa Clara, May 6-8, 2024
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han
BEST PAPER AWARD! Note from Prof. Han: In terms of adoption, AWQ quantized models have more than 16 million downloads on Huggingface.
Punica: Multi-Tenant LoRA Serving
Lequn Chen, Zihao Ye, Yongji Wu, Danyang Zhuo, Luis Ceze, Arvind Krishnamurthy
Proteus: Preserving Model Confidentiality during Graph Optimizations
Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
Atom: Low-Bit Quantization for Efficient and Accurate LLM Serving
Yilong Zhao, Chien-Yu Lin, Kan Zhu, Zihao Ye, Lequn Chen, Size Zheng, Luis Ceze, Arvind Krishnamurthy, Tianqi Chen, Baris Kasikci
SLoRA: Scalable Serving of Thousands of LoRA Adapters
Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning
Gyudong Kim, Mehdi Ghasemi, Soroush Heidari, Seungryong Kim, Young Geun Kim, Sarma Vrudhula, Carole-Jean Wu
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ISCA 2024, Buenos Aires, Argentina, June 29-July 3, 2024
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
BEST PAPER AWARD!
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
DISTINGUISHED ARTIFACT AWARD!
The Dataflow Abstract Machine Simulator Framework
N. Zhang, R. Lacouture, G. Sohn, P. Mure, Q. Zhang, F. Kjolstad, K. Olukotun
DISTINGUISHED ARTIFACT AWARD!
Mind the Gap: Attainable Data Movement and Operational Intensity Bounds for Tensor Algorithms
Q. Huang, P. Tsai, J. Emer, A. Parashar
Atomique: A Quantum Compiler for Reconfigurable Neutral Atom Arrays
H. Wang, P. Liu, D. Tan, Y. Liu, J. Gu, D. Pan, J. Cong, U. Acar, S. Han
MegIS: High-Performance, Energy-Efficient, and Low-Cost Metagenomic Analysis with In-Storage Processing
N. Ghiasi, M. Sadrosadati, H. Mustafa, A. Gollwitzer, C. Firtina, J. Eudine, H. Mao, J. Lindegger, M. Cavlak, M. Alser, J. Park, O. Mutlu
Exploring System-Aware Parallelization for Efficient Large-Scale Machine Learning 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
(MC)^2: Lazy MemCopy at the Memory Controller
A. Kamath, S. Peter
UDP: Utility-Driven Fetch Directed Instruction Prefetching
S. Oh, M. Xu, T. Khan, B. Kasikci, H. Litz
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USENIX ATC, Santa Clara, CA, July 10-12, 2024
Carole-Jean Wu, Meta
KEYNOTE
Yifan Xiong, Yuting Jiang, Ziyue Yang, and Lei Qu, Microsoft Research; Guoshuai Zhao, Shuguang Liu, Dong Zhong, Boris Pinzur, Jie Zhang, Yang Wang, Jithin Jose, Hossein Pourreza, Jeff Baxter, Kushal Datta, Prabhat Ram, Luke Melton, and Joe Chau, Microsoft; Peng Cheng, Yongqiang Xiong, and Lidong Zhou, Microsoft Research
BEST PAPER AWARD!
Starburst: A Cost-aware Scheduler for Hybrid Cloud
Michael Luo, Siyuan Zhuang, Suryaprakash Vengadesan, and Romil Bhardwaj, UC Berkeley; Justin Chang, UC Santa Barbara; Eric Friedman, Scott Shenker, and Ion Stoica, UC Berkeley
DISTINGUISHED ARTIFACT AWARD!
Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention
Bin Gao, National University of Singapore; Zhuomin He, Shanghai Jiaotong University; Puru Sharma, Qingxuan Kang, and Djordje Jevdjic, National University of Singapore; Junbo Deng, Xingkun Yang, Zhou Yu, and Pengfei Zuo, Huawei Cloud
Tingting Xu, Nanjing University; Bengbeng Xue, Yang Song, Xiaomin Wu, Xiaoxin Peng, and Yilong Lyu, Alibaba Group; Xiaoliang Wang, Chen Tian, Baoliu Ye, and Camtu Nguyen, Nanjing University; Biao Lyu and Rong Wen, Alibaba Group;Zhigang Zong, Alibaba Group and Zhejiang University; Shunmin Zhu, Alibaba Group and Tsinghua University
Dan Graur, Oto Mraz, Muyu Li, and Sepehr Pourghannad, ETH Zurich;Chandramohan A. Thekkath, Google; Ana Klimovic, ETH Zurich
Manaf Bin-Yahya, Yifei Zhao, and Hossein Shafieirad, Huawei Technologies Canada; Anthony Ho, Huawei Technologies Canada and University of Waterloo;Shijun Yin and Fanzhao Wang, Huawei Technologies China; Geng Li, Huawei Technologies Canada
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SIGCOMM 2024, Sydney Australia, August 4-8, 2024
Midhul Vuppalapati, Saksham Agarwal, Henry Schuh, Baris Kasikci, Arvind Krishnamurthy, Rachit Agarwal
BEST STUDENT PAPER!
Crux: GPU-Efficient Communication Scheduling for Deep Learning Training
Jiamin Cao, Yu Guan, Kun Qian, Jiaqi Gao, Wencong Xiao, Jianbo Dong, Binzhang Fu, Dennis Cai, Ennan Zhai (Alibaba Cloud)
Lloyd Brown, Albert Gran Alcoz, Frank Cangialosi, Akshay Narayan, Mohammad Alizadeh, Hari Balakrishnan, Eric Friedman, Ethan Katz-Bassett, Arvind Krishnamurthy, Michael Schapira, Scott Shenker
Xieyang Xu, Yifei Yuan, Zachary Kincaid, Arvind Krishnamurthy, Ratul Mahajan, David Walker, Ennan Zhai
Daniel Amir, Nitika Saran, Tegan Wilson, Robert Kleinberg, Vishal Shrivastav, HakimWeatherspoon
Realizing RotorNet: Toward Practical Microsecond Scale Optical Networking
William M. Mellette, Alex Forencich, Rukshani Athapathu, Alex C. Snoeren, George Papen, GeorgePorter
Lloyd Brown, Emily Marx, Dev Bali, Emmanuel Amaro, Debnil Sur, Ezra Kissel, Inder Monga, Ethan Katz-Bassett, Arvind Krishnamurthy, James McCauley, Tejas Narechania, Aurojit Panda, Scott Shenker
Kun Qian, Yongqing Xi, Jiamin Cao, Jiaqi Gao, Yichi Xu, Yu Guan, Binzhang Fu, Xuemei Shi, Fangbo Zhu, Rui Miao, Chao Wang, Peng Wang, Pengcheng Zhang, Xianlong Zeng, Eddie Ruan, ZhipingYao, Ennan Zhai, Dennis Cai
Alexander Krentsel, Nitika Saran, Bikash Koley, Subhasree Mandal, Ashok Narayanan, Sylvia Ratnasamy, Ali Al-Shabibi, Anees Shaikh, Rob Shakir, Ankit Singla, Hakim Weatherspoon
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ACM SIGPLAN Conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH) Pasadena, CA, October 20-25, 2024
Trillions of Formally Verified Authorizations a Day!
Neha Rungta, Amazon Web Services
KEYNOTE
Computing Precise Control Interface Specifications
Eric Campbell, Cornell University, Hossein Hojjat, Tehran Institute for Advanced Studies (TeIAS), Nate Foster, Cornell University and Jane Street
Compilation of Shape Operators on Sparse Arrays
Alexander J Root, Stanford University, Bobby Yan, Stanford University, Peiming Liu, Google Inc, Christophe Gyurgyik, Stanford University, Aart Bik, Google, Inc., Fredrik Kjolstad, Stanford University
Compiler Support for Sparse Tensor Convolutions
Peiming Liu, Google Inc, Alexander J Root, Stanford University, Anlun Xu, Google, Yinying Li, Google, Fredrik Kjolstad, Stanford University, Aart Bik, Google, Inc.
UniSparse: An Intermediate Language for General Sparse Format Customization
Jie Liu, Cornell University, Zhongyuan Zhao, Qualcomm, Zijian Ding, UCLA, Benjamin Brock, Parallel Computing Lab (PCL), Intel, Hongbo Rong, Intel Labs, Zhiru Zhang, Cornell University, USA
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IEEE/ACM International Symposium on Microarchitecture (MICRO-57), Austin, Texas, November 2-6, 2024
Fostering Microarchitecture Innovation in the Age of Data-Driven Intelligence
Gilles Pokam, Intel
KEYNOTE
Accelerating Zero-Knowledge Proofs Through Hardware-Algorithm Co-Design
Nikola Samardzic, Simon Langowski, Srinivas Devadas, Daniel Sanchez (Massachusetts Institute of Technology)
BEST PAPER CANDIDATE!
DelayAVF: Calculating Architectural Vulnerability Factors for Delay Faults
Peter W. Deutsch (MIT); Vincent Quentin Ulitzsch (MIT/TU Berlin); Sudhanva Gurumurthi, Vilas Sridharan (AMD); Joel Emer (MIT/NVIDIA); Mengjia Yan (MIT)
Beehive: A Flexible Network Stack for Direct-Attached Accelerators
Katie Lim, Matthew Giordano, Theano Stavrinos (University of Washington); Jacob Nelson (Microsoft Research); Irene Zhang (Microsoft Research/University of Washington); Baris Kasikci (University of Washington and Google); Thomas Anderson (University of Washington)
Stellar: An Automated Design Framework for Dense and Sparse Spatial Accelerators
Hasan Nazim Genc, Hansung Kim (University of California, Berkeley); Prashanth Ganesh, Sophia Shao (UC Berkeley)
RTL2MµPATH: Multi-μPATH Synthesis with Applications to Hardware Security Verification
Yao Hsiao (Stanford University); Nikos Nikoleris, Artem Khyzha (Arm); Dominic P. Mulligan, Gustavo Petri (Amazon Web Services); Christopher W. Fletcher (University of California, Berkeley); Caroline Trippel (Stanford University)
SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelereators
Mohanad Odema, Luke Chen (University of California Irvine); Hyoukjun Kwon (University of California, Irvine); Mohammad Al Faruque (UC Irvine)
Azul: An Accelerator for Sparse Iterative Solvers Leveraging Distributed On-Chip Memory
Axel Feldmann, Courtney Golden, Yifan Yang (MIT); Joel Emer (MIT/Nvidia); Daniel Sanchez (MIT)
FloatAP: Supporting High-Performance Floating-Point Arithmetic in Associative Processors
Kailin Yang, José F. Martínez (Cornell University)
BreakHammer: Enabling Scalable and Low Overhead RowHammer Mitigations via Throttling Preventive Action Triggering Threads
Oğuzhan Canpolat (TOBB ETÜ); Giray Yaglikci, Ataberk Olgun, Ismail Emir Yuksel (ETH Zurich); Yahya Can Tuğrul (ETH Zurich & TOBB ETÜ); Konstantinos Kanellopoulos (ETH Zurich); Oğuz Ergin (TOBB ETÜ); Onur Mutlu (ETH Zurich & Stanford University)
SambaNova SN40L: Scaling the AI Memory Wall with Dataflow and Composition of Experts
Raghu Prabhakar, Ram Sivaramakrishnan, Darshan Gandhi, Yun Du, Mingran Wang, Xiangyu Song, Kejie Zhang, Tianren Gao, Angela Wang, Joshua Brot, Denis Sokolov, Calvin Leung, Arjun Sabnis, Jiayu Bai, David Jackson, Mark Luttrell, Manish K. Shah, Mark Gottscho, Tuowen Zhao, Karen Li, Urmish Thakker, Edison Chen, Dawei Huang, Swayambhoo Jain, Kevin J. Brown, Kunle Olukotun (SambaNova Systems, Inc)
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ACM Symposium on Cloud Computing 2024 (SoCC '24), Redmond, WA, November 20-22, 2024
En4S: Enabling SLOs in Serverless Storage Systems
Minghao Xie, Chen Qian, Heiner Litz (University of California Santa Cruz)
BEST PAPER AWARD!
Towards Swap-Free, Continuous Ballooning for Fast, Cloud-Based Virtual Machine Migrations
Kevin Alarcón Negy, Tycho Nightingale, Hakim Weatherspoon, Zhiming Shen (Exostellar, inc.)
The Sunk Carbon Fallacy: Rethinking Carbon Footprint Metrics for Effective Carbon-Aware Scheduling
Noman Bashir, Varun Gohil (MIT), Mohammad Shahrad (University of British Columbia), David Irwin (University of Massachusetts, Amherst), Anagha Belavadi Subramanya, Elsa Olivetti, Christina Delimitrou (MIT)
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NeurIPS 2024, The Thirty-Eighth Annual Conference on Neural Information Processing Systems, Vancouver, BC, December 10-15, 2024
Rosalind Picard
INVITED TALK
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio
TEST OF TIME AWARD
Are More LLM Calls All You Need? Towards the Scaling Properties of
Compound AI Systems
Lingjiao Chen · Jared Quincy Davis · Boris Hanin · Peter Bailis · Ion Stoica · Matei A Zaharia · James Zou
Mirco Giacobbe · Daniel Kroening · Abhinandan Pal · Michael Tautschnig
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AWARDS
IFIP Jean-Claude Laprie (JCL) Award in Dependable Computing
Onur Mutlu, ETH Zurich
Jason Cong, UCLA
2024 David Richardson Medal
Radha Nagarajan, Marvell
BEST PAPER AWARDS
ACM SIGARCH/SIGPLAN/SIGOPS ASPLOS INFLUENTIAL PAPER AWARD
ASPLOS 2014
Paragon: QoS-Aware Scheduling for Heterogeneous Datacenters
Christina Delimitrou and Christos Kozyrakis
ISPASS 2024 Best Paper
Tanner Andrulis, Vivienne Sze, Joel S. Emer
MLSys 2024 Best Paper
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han
Note from Prof. Han: In terms of adoption, AWQ quantized models have more than 16 million downloads on Huggingface.
ISCA 2024 Best Paper
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
SIGCOMM 2024 Best Student Paper
Understanding the Host Network
Midhul Vuppalapati, Saksham Agarwal, Henry Schuh, Baris Kasikci, Arvind Krishnamurthy, Rachit Agarwal
ACM SoCC Best Paper
En4S: Enabling SLOs in Serverless Storage Systems
Minghao Xie, Chen Qian, Heiner Litz (University of California Santa Cruz)
NEW APPOINTMENTS
Professor Nate Foster, Cornell, was appointed Associate Dean for Research for Bowers CIS and Vice Chair of DARPA ISAT.
BOOKS
MACHINE LEARNING SYSTEMS with TINYML
Machine Learning Systems with TinyML” offers an accessible entry into the fascinating world of computing that enables machine learning, with a special focus on its implementation in resource-constrained environments using TinyML. This is an open source project on GitHub; contributors are welcome! See Prof. Vijay Janapa Reddy’s podcast and this short IEEE paper, which explores ML systems engineering as a formal discipline.
BLOGS
August 1, 2024
Designing Computer Systems for Sustainability
by Carole Jean-Wu, Tamar Eilam, Babak Falsafi, Gage Hills, and Srilatha Manne
July 24, 2024
Remembering Arvind
by Friends, Colleagues, and Students of Arvind
June 13, 2024
ACE Center: Energy-efficient Distributed Computing for the Next Decade and Beyond
by Josep Torrellas
NEWS ITEMS
November 29, 2024
Alibaba releases Qwen with Questions, an open reasoning model that beats o1-preview
November 12, 2024
Amazon Puts $110M Into Academic Generative AI Research
November 6, 2024
AMD Launches New CPUs, GPUs And More Across Datacenter, AI And PC
Sept 25, 2024
Chip giant Nvidia acquires OctoAI, a Seattle startup that helps companies run AI models
July 31, 2024
Marvell Delivers On CXL’s Promise Of Efficient, Scalable Data Centers
June 3, 2024
Computex 2024: The Battle for AI Copilot PCs Begins
IAP Workshop Testimonials
Professor Christos Kozyrakis, Stanford - “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 Heiner Litz, UC Santa Cruz - "The IAP workshops represent extremely valuable events for all attendees including industry members, students and faculty. On my side, multiple project collaborations and student internships have evolved from these meetings leading to a win-win-win situation for all participants.”
Professor Ana Klimovic, ETH Zurich - “I have attended three IAP workshops as a PhD student at Stanford and was 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. Nathan Pemberton, Scientist, Amazon Web Services - "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."
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Best,
Jim Ballingall
Executive Director
Industry-Academia Partnership (IAP)
www.industry-academia.org
jim.ballingall@gmail.com
cel: 408-212-1035
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