Software-Defined Hardware & Systems Co-Design | Kisaco Research

AI acceleration is a full stack effort and involves a multidisciplinary and holistic approach to design and optimization.

The field of deep learning has gained substantially from co-design concepts across the AI technology stack. The simultaneous design and optimization of hardware and software has led to new algorithms, numerical optimizations, and AI hardware. 

Looking at the AI stack for workloads like computer vision, NLP and Ads, in both a vertical and horizontal sense, there are significant opportunities and challenges for optimization through co-design. This panel will focus on software-defined chips and systems for AI (specs & evaluation, datacenter & edge) and look at the systems-level approach to co-design, including compilers and runtime etc.

Session Topics: 
Chip Design
Novel AI Hardware
Systems Design
Speaker(s): 

Author:

Xiaoyong Liu

Director, AI Platform
Alibaba

Xiaoyong Liu

Director, AI Platform
Alibaba

Author:

Kim Hazelwood

Director, Engineering
Meta

Kim Hazelwood is an engineering leader whose expertise lies at the intersection of scalable computer systems and applied machine learning. Her roles at Meta have included multiple engineering organizational leadership roles across Infrastructure and Research. Prior to Facebook, Kim held positions including Director of Research at Yahoo Labs, Software Engineer in the datacenter division of Google, Research Scientist at Intel, and tenured Associate Professor of Computer Science at the University of Virginia. Kim holds a PhD in Computer Science from Harvard University and has authored over 50 publications and one book. She is a recipient of the MIT "Top 35 Innovators under 35"​ award, the ACM SIGPLAN "Test of Time" Award, the Anita Borg Early Career Award, and an NSF Career Award. She currently serves on the Board of Directors for the Computing Research Association. 

Kim Hazelwood

Director, Engineering
Meta

Kim Hazelwood is an engineering leader whose expertise lies at the intersection of scalable computer systems and applied machine learning. Her roles at Meta have included multiple engineering organizational leadership roles across Infrastructure and Research. Prior to Facebook, Kim held positions including Director of Research at Yahoo Labs, Software Engineer in the datacenter division of Google, Research Scientist at Intel, and tenured Associate Professor of Computer Science at the University of Virginia. Kim holds a PhD in Computer Science from Harvard University and has authored over 50 publications and one book. She is a recipient of the MIT "Top 35 Innovators under 35"​ award, the ACM SIGPLAN "Test of Time" Award, the Anita Borg Early Career Award, and an NSF Career Award. She currently serves on the Board of Directors for the Computing Research Association. 

Author:

Dr. Charles Fan

CEO and Co-Founder
MemVerge

Charles Fan is CEO and co-founder of MemVerge. Prior to MemVerge, Charles was the CTO of Cheetah Mobile leading its global technology teams, and an SVP/GM at VMware, founding the storage business unit that developed the Virtual SAN product. Charles also worked at EMC and was the founder of the EMC China R&D Center. Charles joined EMC via the acquisition of Rainfinity, where he was a co-founder and CTO. Charles received his Ph.D. and M.S. in Electrical Engineering from the California Institute of Technology, and his B.E. in Electrical Engineering from the Cooper Union.

Dr. Charles Fan

CEO and Co-Founder
MemVerge

Charles Fan is CEO and co-founder of MemVerge. Prior to MemVerge, Charles was the CTO of Cheetah Mobile leading its global technology teams, and an SVP/GM at VMware, founding the storage business unit that developed the Virtual SAN product. Charles also worked at EMC and was the founder of the EMC China R&D Center. Charles joined EMC via the acquisition of Rainfinity, where he was a co-founder and CTO. Charles received his Ph.D. and M.S. in Electrical Engineering from the California Institute of Technology, and his B.E. in Electrical Engineering from the Cooper Union.

Author:

Zaid Kahn

GM, Cloud AI & Advanced Systems Engineering
Microsoft

Zaid is currently GM in Cloud Hardware Infrastructure Engineering where he leads a team focusing on advanced architecture and engineering efforts for AI. He is passionate about building balanced teams of artists and soldiers that solve incredibly difficult problems at scale.

Prior to Microsoft Zaid was head of infrastructure engineering at LinkedIn responsible for all aspects of engineering for Datacenters, Compute, Networking, Storage and Hardware. He also lead several software development teams spanning from BMC, network operating systems, server and network fleet automation to SDN efforts inside the datacenter and global backbone including edge. He introduced the concept of disaggregation inside LinkedIn and pioneered JDM with multiple vendors through key initiatives like OpenSwitch, Open19 essentially controlling destiny for hardware development at LinkedIn. During his 9 year tenure at LinkedIn his team scaled network and systems 150X, members from 50M to 675M, and hiring someone every 7 seconds on the LinkedIn Platform.

Prior to LinkedIn Zaid was Network Architect at WebEx responsible for building the MediaTone network and later I built a startup that built a pattern recognition security chip using NPU/FPGA. Zaid holds several patents in networking and SDN and is also a recognized industry leader. He previously served as a board member of the Open19 Foundation and San Francisco chapter of Internet Society. Currently he serves on DE-CIX and Pensando advisory boards.

Zaid Kahn

GM, Cloud AI & Advanced Systems Engineering
Microsoft

Zaid is currently GM in Cloud Hardware Infrastructure Engineering where he leads a team focusing on advanced architecture and engineering efforts for AI. He is passionate about building balanced teams of artists and soldiers that solve incredibly difficult problems at scale.

Prior to Microsoft Zaid was head of infrastructure engineering at LinkedIn responsible for all aspects of engineering for Datacenters, Compute, Networking, Storage and Hardware. He also lead several software development teams spanning from BMC, network operating systems, server and network fleet automation to SDN efforts inside the datacenter and global backbone including edge. He introduced the concept of disaggregation inside LinkedIn and pioneered JDM with multiple vendors through key initiatives like OpenSwitch, Open19 essentially controlling destiny for hardware development at LinkedIn. During his 9 year tenure at LinkedIn his team scaled network and systems 150X, members from 50M to 675M, and hiring someone every 7 seconds on the LinkedIn Platform.

Prior to LinkedIn Zaid was Network Architect at WebEx responsible for building the MediaTone network and later I built a startup that built a pattern recognition security chip using NPU/FPGA. Zaid holds several patents in networking and SDN and is also a recognized industry leader. He previously served as a board member of the Open19 Foundation and San Francisco chapter of Internet Society. Currently he serves on DE-CIX and Pensando advisory boards.

Author:

Diana Marculescu

Professor & Department Chair, Electrical and Computer Engineering
University of Texas

Diana Marculescu is Department Chair, Cockrell Family Chair for Engineering Leadership #5, and Professor, Motorola Regents Chair in Electrical and Computer Engineering #2, at the University of Texas at Austin.

Prior to joining UT Austin in December 2019, she was the David Edward Schramm Professor of Electrical and Computer Engineering, the Founding Director of the College of Engineering Center for Faculty Success (2015-2019) and has served as Associate Department Head for Academic Affairs in Electrical and Computer Engineering (2014-2018), all at Carnegie Mellon University.

She received the Dipl.Ing. degree in computer science from the Polytechnic University of Bucharest, Bucharest, Romania (1991), and the Ph.D. degree in computer engineering from the University of Southern California, Los Angeles, CA (1998). Her research interests include energy- and reliability-aware computing, hardware aware machine learning, and computing for sustainability and natural science applications.

Diana was a recipient of the National Science Foundation Faculty Career Award (2000-2004), the ACM SIGDA Technical Leadership Award (2003), the Carnegie Institute of Technology George Tallman Ladd Research Award (2004), and several best paper awards. She was an IEEE Circuits and Systems Society Distinguished Lecturer (2004-2005) and the Chair of the Association for Computing Machinery (ACM) Special Interest Group on Design Automation (2005-2009). Diana chaired several conferences and symposia in her area and is currently an Associate Editor for IEEE Transactions on Computers. She was selected as an ELATE Fellow (2013-2014), and is the recipient of an Australian Research Council Future Fellowship (2013-2017), the Marie R. Pistilli Women in EDA Achievement Award (2014), and the Barbara Lazarus Award from Carnegie Mellon University (2018). Diana is a Fellow of ACM and IEEE.

Diana Marculescu

Professor & Department Chair, Electrical and Computer Engineering
University of Texas

Diana Marculescu is Department Chair, Cockrell Family Chair for Engineering Leadership #5, and Professor, Motorola Regents Chair in Electrical and Computer Engineering #2, at the University of Texas at Austin.

Prior to joining UT Austin in December 2019, she was the David Edward Schramm Professor of Electrical and Computer Engineering, the Founding Director of the College of Engineering Center for Faculty Success (2015-2019) and has served as Associate Department Head for Academic Affairs in Electrical and Computer Engineering (2014-2018), all at Carnegie Mellon University.

She received the Dipl.Ing. degree in computer science from the Polytechnic University of Bucharest, Bucharest, Romania (1991), and the Ph.D. degree in computer engineering from the University of Southern California, Los Angeles, CA (1998). Her research interests include energy- and reliability-aware computing, hardware aware machine learning, and computing for sustainability and natural science applications.

Diana was a recipient of the National Science Foundation Faculty Career Award (2000-2004), the ACM SIGDA Technical Leadership Award (2003), the Carnegie Institute of Technology George Tallman Ladd Research Award (2004), and several best paper awards. She was an IEEE Circuits and Systems Society Distinguished Lecturer (2004-2005) and the Chair of the Association for Computing Machinery (ACM) Special Interest Group on Design Automation (2005-2009). Diana chaired several conferences and symposia in her area and is currently an Associate Editor for IEEE Transactions on Computers. She was selected as an ELATE Fellow (2013-2014), and is the recipient of an Australian Research Council Future Fellowship (2013-2017), the Marie R. Pistilli Women in EDA Achievement Award (2014), and the Barbara Lazarus Award from Carnegie Mellon University (2018). Diana is a Fellow of ACM and IEEE.