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, hardware acceleration, operating systems, networking, security, storage and data management - all in the context of distributed systems.

IAP WORKSHOPS - 2022 and 2023

CORNELL AI and CLOUD WORKSHOP


Friday, October 14, 2022


Cornell University, Ithaca, New York

Cornell PhD student Daniel Amir (front center in photo) won the Best Poster Award for "Optimal Oblivious Reconfigurable Networks", co-authored by Tegan Wilson, Bobby Kleinberg, Rachit Agarwal, Hakim Weatherspoon, and Vishal Shrivastav.


Speakers on October 14 (listed alphabetically by last name)

  • Prof. Ken Birman, Cornell
  • Prof. Nate Foster, Cornell
  • Dr. Jiaqi Gao, Alibaba
  • Prof. Carla Gomes, Cornell
  • Dr. Rick Kessler, Marvell
  • Dr. Jian Li, Futurewei
  • Prof. José Martínez, Cornell
  • Prof. Francesca Parise, Cornell
  • Dr. Antigoni Polychroniadou, JP Morgan Chase
  • Dr. Serdar Tasiran, Amazon Web Services
  • Prof. Robbert van Renesse, Cornell & Exotanium


This was the fourth Cloud Workshop hosted by Cornell. Please see the Cornell 2022 Workshop web page for the speaker bios, abstracts and videos of the presentations.

BERKELEY/STANFORD/UCSC WORKSHOP ON THE FUTURE OF CLOUD COMPUTING


Wednesday, May 11, 2022


Stanford University

Partha Ranganathan, Google VP and Engineering Fellow opens the morning session with his talk "Cloudy with a Chance of ML"


Speakers on May 11 (listed alphabetically by last name): 

  • Dr. Niket Agarwal, Meta, Principal Software Engineer
  • Prof. Peter Alvaro, UCSC
  • Dr. Ulf Hanebutte, Marvell, Performance Architect
  • Prof. Heiner Litz, UCSC 
  • ​Dr. Harry Liu, Alibaba, Director of Network R&D
  • Dr. Richard New, Western Digital, VP of Research
  • Dr. Gilles Pokam, Intel, Principal Engineer
  • Prof. Andrew Quinn, UCSC
  • Prof. Priyanka Raina, Stanford
  • Dr. Partha Ranganathan, Google, VP and Engineering Fellow


This was the fourth Cloud Workshop hosted by Stanford. Please see the Workshop web page for the speaker bios, abstracts and videos of the presentations.

COMING in SPRING 2023


UCSD AI and CLOUD WORKSHOP


With UCI, UCLA, UCR, and USC


UCSD Campus

La Jolla, CA


Organized by Prof. Hadi Esmaeilzadeh and the IAP. 


Please watch for IAP Newsletters and our website for further updates on the date and agenda.

SELECT CONFERENCES and PUBLICATIONS in 2H 2022


ISCA 2022, New York City, June 18-22, 2022

Axiomatic Hardware-Software Contracts for Security

Nicholas Mosier, Hanna Lachnitt (Stanford University); Hamed Nemati (Stanford University and CISPA Helmholtz Center for Information Security); Caroline Trippel (Stanford University)


CraterLake: A Hardware Accelerator for Efficient Unbounded Computation on Encrypted Data

Nikola Samardzic, Axel Feldmann, Aleksandar Krastev (Massachusetts Institute of Technology); Nathan Manohar (IBM T.J. Watson); Nicholas Genise (SRI International); Srinivas Devadas (Massachusetts Institute of Technology); Karim Eldefrawy (SRI International); Chris Peikert (University of Michigan); Daniel Sanchez (Massachusetts Institute of Technology)


Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems using Online Reinforcement Learning

Gagandeep Singh, Rakesh Nadig, Jisung Park, Rahul Bera, Nastaran Hajinazar (ETH Zurich); David Novo (LIRMM, Univ Montpellier, CNRS); Juan Gomez-Luna (ETH Zurich); Sander Stuijk, Henk Corporaal (Eindhoven University of Technology); Onur Mutlu (ETH Zurich)


Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training

Mark Zhao, Niket Agarwal, Aarti Basant, Bugra Gedik, Satadru Pan, Mustafa Ozdal, Rakesh Komuravelli, Jerry Pan, Tianshu Bao, Haowei Lu, Sundaram Narayanan, Jack Langman, Kevin Wilfong, Harsha Rastogi, Carole-Jean Wu (Meta); Christos Kozyrakis (Stanford University); Parik Pol (Meta)


Accelerating Database Analytic Query Workloads Using an Associative Processor

Helena Caminal (Cornell University); Yannis Chronis (University of Wisconsin-Madison); Tianshu Wu (Cornell University); Jignesh Patel (University of Wisconsin-Madison); José Martínez (Cornell University)


SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping

Damla Senol Cali (Bionano Genomics); Konstantinos Kanellopoulos, Joel Lindegger (ETH Zurich); Zülal Bingöl (Bilkent University); Gurpreet S Kalsi (Intel Labs); Ziyi Zuo (Carnegie Mellon University); Can Firtina, Meryem Banu Cavlak, Jeremie Kim, Nika Mansouri Ghiasi, Gagandeep Singh, Juan Gómez-Luna, Nour Almadhoun Alserr, Mohammed Alser (ETH Zurich); Sreenivas Subramoney (Intel Labs); Can Alkan (Bilkent University); Saugata Ghose (University of Illinois Urbana-Champaign); Onur Mutlu (ETH Zurich)


Thermometer: Profile-Guided BTB Replacement for Data Center Applications

Shixin Song, Tanvir Ahmed Khan, Sara Mahdizadeh Shahri (University of Michigan); Akshitha Sriraman (Carnegie Mellon University / Google); Niranjan K Soundararajan, Sreenivas Subramoney (Intel Labs); Daniel A. Jiménez (Texas A&M University); Heiner Litz (University of California, Santa Cruz); Baris Kasikci (University of Michigan)


HiveMind: A Hardware-Software System Stack for Serverless Edge Swarms

Liam Patterson, David Pigorovsky, Brian Dempsey, Nikita Lazarev, Aditya Shah, Clara Steinhoff, Ariana Bruno, Justin Hu, Christina Delimitrou (Cornell University)


ACT: Designing Sustainable Computer Systems With An Architectural Carbon Modeling Tool

Udit Gupta (Harvard University/Facebook); Mariam Elgamal, Gage Hills (Harvard University); Gu-Yeon Wei (Harvard University / Samsung); Hsien-Hsin S. Lee (Meta AI); David Brooks (Harvard University); Carole-Jean Wu (Facebook/ASU)


Accelerating Attention through Gradient-Based Learned Runtime Pruning

Zheng Li, Soroush Ghodrati (University of California, San Diego); Amir Yazdanbakhsh (Google Research); Hadi Esmaeilzadeh, Mingu Kang (University of California, San Diego)

USENIX ATC, Carlsbad, CA, July 11-13, 2022

Cachew: Machine Learning Input Data Processing as a Service

Dan Graur, Damien Aymon, Dan Kluser, and Tanguy Albrici, ETH Zurich; Chandramohan A. Thekkath, Google; Ana Klimovic, ETH Zurich


Hashing Design in Modern Networks: Challenges and Mitigation Techniques

Yunhong Xu, Texas A&M University; Keqiang He and Rui Wang, Google; Minlan Yu, Harvard University; Nick Duffield, Texas A&M University; Hassan Wassel, Shidong Zhang, Leon Poutievski, Junlan Zhou, and Amin Vahdat, Google


The Computing and Information Science and Engineering Landscape: A Look Forward

Margaret Martonosi, National Science Foundation


FpgaNIC: An FPGA-based Versatile 100Gb SmartNIC for GPUs

Zeke Wang, Hongjing Huang, Jie Zhang, and Fei Wu, Zhejiang University; Gustavo Alonso, ETH Zurich


Amazon DynamoDB: A Scalable, Predictably Performant, and Fully Managed NoSQL Database Service

Mostafa Elhemali, Niall Gallagher, Nicholas Gordon, Joseph Idziorek, Richard Krog, Colin Lazier, Erben Mo, Akhilesh Mritunjai, Somu Perianayagam ,Tim Rath, Swami Sivasubramanian, James Christopher Sorenson III, Sroaj Sosothikul, Doug Terry, Akshat Vig, Amazon Web Services


ZNSwap: un-Block your Swap

Shai Bergman, Technion; Niklas Cassel and Matias Bjørling, Western Digital; Mark Silberstein, Technion


Trustworthy Open Source: The Consequences of Success

Eric Brewer, VP Infrastructure, Google Fellow and Professor Emeritus, UC Berkeley

SIGCOMM 2022, Amsterdam, August 22-26, 2022


SurgeProtector: Mitigating Temporal Algorithmic Complexity Attacks using Adversarial Scheduling

Nirav Atre, Hugo Sadok, Erica Chiang, Weina Wang, Justine Sherry (Carnegie Mellon University)


From Luna to Solar: The Evolutions of the Compute-to-Storage Networks in Alibaba Cloud

Rui Miao, Lingjun Zhu, Shu Ma, Kun Qian, Shujun Zhuang, Bo Li, Shuguang Cheng, Jiaqi Gao, Yan Zhuang, Pengcheng Zhang, Rong Liu, Chao Shi, Binzhang Fu, Jiaji Zhu, Jiesheng Wu, Dennis Cai, Hongqiang Harry Liu (Alibaba Group)


Towards µs Tail Latency and Terabit Ethernet: Disaggregating the Host Network Stack

Qizhe Cai, Midhul Vuppalapati (Cornell University), Jaehyun Hwang (Sungkyunkwan University), Christos Kozyrakis (Stanford University), Rachit Agarwal (Cornell University)


dcPIM: Near-Optimal Proactive Datacenter Transport

Qizhe Cai, Mina Tahmasbi Arashloo, Rachit Agarwal (Cornell University)


SwitchV: Automated SDN Switch Validation with P4 Models

Kinan Dak Albab (Brown University), Steffen Smolka, Jonathan Dilorenzo, Ali Kheradmand, Konstantin Weitz, Stefan Heule (Google), Minlan Yu, Jiaqi Gao (Harvard University), Muhammad Tirmazi (N/A)


Practical GAN-based Synthetic IP Header Trace Generation using NetShare

Yucheng Yin, Zinan Lin, Minhao Jin, Giulia Fanti, Vyas Sekar (Carnegie Mellon University)


Continuous In-Network Round-Trip Time Monitoring

Satadal Sengupta, Hyojoon Kim, Jennifer Rexford (Princeton University)


Thanos: Programmable Multi-Dimensional Table Filters for Line Rate Network Functions

Vishal Shrivastav (Purdue University)

HOT CHIPS, Santa Clara, CA, August 21-23, 2022


HALO: A Flexible and Low Power Processing Fabric for Brain-Computer Interfaces

Abhishek Bhattacharjee & Rajit Manohar, Yale University 


Kraken: A Direct Event/Frame-Based Multi-sensor Fusion SoC for Ultra-Efficient Visual Processing in Nano-UAVs

Alfio Di Mauro, ETH Zurich 


Amber: Coarse-Grained Reconfigurable Array-Based SoC for Dense Linear Algebra Acceleration

Kathleen Feng, Stanford


Groq Software-Defined Scale-out Tensor Streaming Multi-Processor

Dennis Abts, Groq 


DOJO: The Microarchitecture of Tesla’s Exa-Scale Computer

Emil Talpes, Tesla 


Cerebras Architecture Deep Dive: First Look Inside the HW/SW Co-Design for Deep Learning

Sean Lie, Cerebras


Semiconductors Run the World

Pat Gelsinger, Intel


NVIDIA’s Hopper GPU: Scaling Performance

Jack Choquette & Ronny Krashinsky, NVIDIA 


AMD Instinct™ MI200 Series Accelerator and Node Architectures

Alan Smith & Norman James, AMD 


Intel’s Ponte Vecchio GPU: Architecture, System and Software

Hong Jiang, Intel 


Biren BR100 GPGPU: Accelerating Datacenter Scale AI Computing

Mike Hong & Lingjie Xu, Biren Technology

MLSys 2022, August 27-Sept 1, 2022, Santa Clara, CA


Plumber: Diagnosing and Removing Performance Bottlenecks in Machine Learning Data Pipelines 

Michael Kuchnik, Ana Klimovic, Jiri Simsa, Virginia Smith, George Amvrosiadis


ML-EXray: Visibility into ML Deployment on the Edge Hang

Qiu, Ioanna Vavelidou, Jian Li, Evgenya Pergament, Pete Warden, Sandeep Chinchali, Zain Asgar, Sachin Katti


MLPerf Mobile Inference Benchmark: An Industry-Standard Open-Source Machine Learning Benchmark for On-Device AI 

Vijay Janapa Reddi, David Kanter, Peter Mattson, Jared Duke, Thai Nguyen, Ramesh Chukka, Ken Shiring, Koan-Sin Tan, Mark Charlebois, William Chou, Mostafa El-Khamy, Jungwook Hong, Tom St John, Cindy Trinh, Michael Buch, Mark Mazumder, Relja Markovic, Thomas Atta, Fatih Cakir, Masoud Charkhabi, Xiaodong Chen, Cheng-Ming Chiang, Dave Dexter, Terry Heo, Guenther Schmuelling, Maryam Shabani, Dylan Zika


Sustainable AI: Environmental Implications, Challenges and Opportunities 

Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood


PAPAYA: Practical, Private, and Scalable Federated Learning 

Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek


SRIFTY: Swift and Thrifty Distributed Neural Network Training on the Cloud 

Liang Luo, Peter West, Pratyush Patel, Arvind Krishnamurthy, Luis Ceze


DietCode: Automatic Optimization for Dynamic Tensor Programs 

Bojian Zheng, Ziheng Jiang, Cody Hao Yu, Haichen Shen, Joshua Fromm, Yizhi Liu, Yida Wang, Luis Ceze, Tianqi Chen, Gennady Pekhimenko


IEEE/ACM International Symposium on Microarchitecture (MICRO-55), Chicago, Illinois, October 1-5, 2022 


Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction

Rahul Bera, Konstantinos Kanellopoulos (ETH Zürich); Shankar Balachandran (Intel); David Novo (LIRMM / University of Montpellier / CNRS); Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu (ETH Zürich)


big.VLITTLE: On-Demand Data-Parallel Acceleration for Mobile Systems on Chip

Tuan Ta, Khalid Al-Hawaj, Nick Cebry, Yanghui Ou, Eric Hall, Courtney Golden, Christopher Batten (Cornell University)


AQUA: Scalable Rowhammer Mitigation by Quarantining Aggressor Rows at Runtime

Anish Saxena, Gururaj Saileshwar (Georgia Institute of Technology); Prashant J. Nair (University of British Columbia); Moinuddin Qureshi (Georgia Institute of Technology)


Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles

Srivatsan Krishnan (Harvard); Zishen Wan (Georgia Institute of Technology); Kshitij Bhardwaj (LLNL); Paul Whatmough (Arm / Harvard University); Aleksandra Faust (Google Research); Sabrina M. Neuman (Harvard University / Massacuhsetts Institute of Technology); Gu-Yeon Wei, David Brooks (Harvard University); Vijay Janapa Reddi (Harvard University / University of Texas at Austin / Google)


Datamime: Generating Representative Benchmarks by Automatically Synthesizing Datasets

Hyun Ryong Lee, Daniel Sanchez (Massachusetts Institute of Technology)


Sparseloop: An Analytical Approach to Sparse Tensor Accelerator Modeling

Yannan Nellie Wu (Massachusetts Institute of Technology); Po-An Tsai, Angshuman Parashar (NVIDIA); Vivienne Sze (Massachusetts Institute of Technology); Joel Emer (Massachusetts Institute of Technology / NVIDIA)

ACM Symposium on Cloud Computing 2022 (SoCC '22), San Francisco, CA, November 7-11, 2022


Leveraging Application Classes to Save Power in Highly-Utilized Data Centers

Kostis Kaffes (Stanford University); Dragos Sbirlea, Yiyan Lin, David Lo (Google); Christos Kozyrakis (Stanford University, Google)


High availability in cheap distributed key value storage

Thomas Kim, Daniel L.-K. Wong, Gregory R. Ganger (Carnegie Mellon University); Michael Kaminsky (BrdgAI / Carnegie Mellon University); David G. Andersen (Carnegie Mellon University)


Janus: Latency-Aware Provisioning and Scaling for Prediction Serving Pipelines

Daniel Crankshaw (Microsoft Research); Gur-Eyal Sela (UC Berkeley); Xiangxi Mo (UC Berkeley, Anyscale); Corey Zumar (DataBricks); Ion Stoica, Joseph Gonzalez (UC Berkeley); Alexey Tumanov (Georgia Tech)


Photons: Lambdas on a diet

Vojislav Dukic, Rodrigo Bruno (ETH Zurich); Ankit Singla (ETH Zürich); Gustavo Alonso (ETH Zurich)

SUPER COMPUTING 2022, Dallas, Texas, November 15-17, 2022


Parla: A Python Orchestration System for Heterogeneous Architectures

Hochan Lee, William Ruys, Ian Henriksen, Arthur Peters, Yineng Yan, Sean Stephens, Bozhi You, Henrique Fingler, Martin Burtscher, Milos Gligoric, Karl Schulz, Keshav Pingali, Christopher J. Rossbach, Mattan Erez, George Biros


ProbGraph: High-Performance and High-Accuracy Graph Mining

Maciej BestaCesare MiglioliPaolo Sylos LabiniJakub TětekPatrick IffRaghavendra KanakagiriSaleh AshkboosKacper JandaMichal PodstawskiGrzegorz KwasniewskiNiels GleinigFlavio VellaOnur MutluTorsten Hoefler


SpDISTAL: Compiling Distributed Sparse Tensor Computations

Rohan Yadav, Alex Aiken, Fredrik Kjolstad


Mapping Out the HPC Dependency Chaos

Farid Zakaria, Thomas Scogland, Todd Gamblin, Carlos Maltzahn

ACM SIGPLAN Conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH) with Object-Oriented Programming, Systems, Languages & Applications (OOPSLA), Auckland, New Zealand, December 5-10, 2022


Katara: Synthesizing CRDTs with Verified Lifting

Shadaj Laddad University of California at Berkeley, Conor Power University of California at Berkeley, Mae Milano University of California at Berkeley, Alvin Cheung University of California at Berkeley, Joseph M. Hellerstein University of California at Berkeley

RISC-V SUMMIT, San Jose, CA, December 12-15, 2022


Keynote: Lip-Bu Tan, Founder and Chairman, Walden International; Founding Managing Partner of Celesta Capital & Walden Catalyst Ventures; Executive Chairman, Cadence Design Systems, Inc. 


Keynote: Krste Asanović, Professor, UC Berkeley & Chair of RISC-V International 


Panel: It Takes a Village… to Build an Ecosystem: Bob Brennan, Intel; Amber Huffman, Google; Dan Mender, Green Hills Software; Peter Lewin, Imagination Technologies; Rob Aitken, Synopsys; Phil Dworsky, SiFive

Apache TVM and Deep Learning Compilation Conference, Seattle, WA

Rescheduled from December 2022 to March 13-17, 2023

AWARDS


NVMW 2022 Persistent Impact Prize:  Onur Mutlu, Benjamin Lee, Engin Ipek, and Doug Burger, received the NVMW 2022 Persistent Impact Prize for their 2009 ISCA paper on Architecting Phase Change Memory as a Scalable DRAM Alternative.  The prize was awarded to the ISCA 2009 paper “in recognition of its seminal contribution to understanding how non-volatile memories might replace conventional DRAM. It also played a critical role in introducing Phase Change Memory (PCM) technology to the architecture community, spawning a wide range of follow-on work.”


2022 SIGOPS Mark Weiser Award: David Anderson, CMU

The Mark Weiser Award is given to an individual who has demonstrated creativity and innovation in operating systems research. 


BEST PAPER AWARDS


ASPLOS Top Picks: Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices

Yu Gan, Mingyu Liang (Cornell University); Sundar Dev, David Lo (Google); Christina Delimitrou (Cornell University)


MICRO 2022: Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction

Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu


SUPER COMPUTING 2022: ProbGraph: High-Performance and High-Accuracy Graph Mining

Maciej BestaCesare MiglioliPaolo Sylos LabiniJakub TětekPatrick IffRaghavendra KanakagiriSaleh AshkboosKacper JandaMichal PodstawskiGrzegorz KwasniewskiNiels GleinigFlavio VellaOnur MutluTorsten Hoefler


GRANTS and FUND RAISING


Heiner Litz and Ricardo Sanfelice (UCSC)

$6M NSF grant for cyber-physical systems project will enable engineers to explore the next generation of transportation systems


Hakim Weatherspoon and Robbert van Renesse (Cornell)

Exotanium raises $12M to optimize cloud efficiency while reducing costs by up to 90%


PROJECTS


RISC-V on Enzian, October 13, 2022

The Enzian team brought up the Rocket RISC-V core on Enzian’s FPGA. They are able to load an image from the CPU side, across ECI, directly into the FPGA’s DRAM, and then boot into Linux on the RISC-V core.


Enzian is designed for computer systems software research. An Enzian node has a big server-class Marvell CPU closely coupled to a large Xilinx FPGA, in cache coherence with ample main memory and network bandwidth on both sides. The team has 9 (nine!) working Enzian machines in Zurich networked and in use by researchers around the world. 



NEWS ITEMS


November 26, 2022

Re:Invent 2022 marks the next chapter in data and cloud


November 8, 2022

Exotanium raises $12M to optimize cloud efficiency while reducing costs by up to 90%


October 14, 2022

Big Tech Continues To Buy Semiconductors at Record Levels in 2022


September 16, 2022

The AI gold rush is alive in Silicon Valley


August 15, 2022

CXL Dominated the 2022 Flash Memory Summit 


July 18, 2022

Nanomagnets Can Choose a Wine, and Could Slake AI's Thirst for Energy


June 21, 2022

OPI Project Aims to Standardize DPUs and IPUs for Industry Adoption


May 19, 2022

Alibaba Opens AI-Focused Data Center in Germany



IAP Workshop Testimonials

(from the 2018 Stanford-UCSC Cloud Workshop)

 

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.” 


Ana Klimovic, PhD student, Stanford - “I have attended three IAP workshops 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." 

 

Nathan Pemberton, PhD student, UC Berkeley - "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." 


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 © 2013-2022 Industry-Academia Partnership