[Quantum-ms] [Seminar] EE Faculty Candidate Lecture Tmrw at 11:40am

[Columbia EE Events]

[image: Left-aligned blue cuee logo.png]

*Please join us for the EE/CS faculty candidate lecture on 4/8!*

*When: *4/8, Tuesday, 11:40am - 12:40pm
*Where: *CEPSR 750, also via zoom
<https://columbiauniversity.zoom.us/j/4419920270#success >.
*Who:* Dr. Olivia Hsu
*Title: *From Language to Silicon: Programming Systems for Sparse
Accelerators

*Abstract:*
In this era of specialization, modern hardware development focuses on
domain-specific accelerator design due to the plateau in technology scaling
combined with a continual need for performance. However, domain-specific
programming systems for these accelerators require extreme engineering
effort, and their complexity has largely caused them to lag behind.
Fundamentally, the widespread usability, proliferation, and democratization
of domain-specific accelerators hinge on their programming systems,
especially when targeting new domains.

This talk presents research on accelerator programming systems for the
emerging domain of sparse computation. The first system, the Sparse
Abstract Machine (SAM), introduces a unified abstract machine model and
compiler abstraction for sparse dataflow accelerators. SAM defines a novel
streaming representation and abstract dataflow interfaces that serve as an
abstraction to decouple sparse accelerator implementations from their
programs, similar to a stable ISA but for dataflow. The second system,
Mosaic, introduces modular and portable compilation solutions that can
leverage heterogeneous sparse accelerators and high-performance systems
within the same system. These systems are a first step towards usable and
programmable heterogeneous hardware acceleration for all. I will conclude
by discussing the next steps to reach this goal, which include programming
systems for accelerators in other domains and interoperation between
accelerators across domains.


Bio:
Olivia Hsu is a final-year Ph.D. candidate at Stanford University in the
Department of Computer Science, advised by Professors Kunle Olukotun and
Fredrik Kjolstad. She received her B.S. in Electrical Engineering and
Computer Science (EECS) at UC Berkeley. Her broad research interests
include computer architecture, computer and programming systems, compilers,
programming languages, and digital circuits/VLSI. Olivia is a 2024 Rising
Star in EECS and an NSF Graduate Research Fellow, and her research won a
distinguished paper award at PLDI 2023. To learn more about her work,
please visit her website at https://urldefense.proofpoint.com/v2/url?u=https-3A__cs.stanford.edu_-7Eowhsu&d=DwIBaQ&c=009klHSCxuh5AI1vNQzSO0KGjl4nbi2Q0M1QLJX9BeE&r=SD-9ztpHDQVkXLFc0zdc9RZWqGhdQ2vAJZ0O73eMlt0&m=KXv9by_AD32DaMiMteHWbXlvmw4O5LytNJye5uk9aqyjVEIFUTXiD2hKKpxo9LI-&s=B4ZUJLcgb9htnco2LiYEGoMZbZoVx1XQRQCBpjRfhTE&e= .
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