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

[Columbia EE Events]

Hi all, just a reminder the seminar will start at 11:40am at CEPSR 750. See
you soon!

On Mon, Apr 7, 2025 at 1:15 PM Columbia EE Events <ee-events at ee.columbia.edu>
wrote:

> [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=DwIFaQ&c=009klHSCxuh5AI1vNQzSO0KGjl4nbi2Q0M1QLJX9BeE&r=SD-9ztpHDQVkXLFc0zdc9RZWqGhdQ2vAJZ0O73eMlt0&m=LAME78veFWoRxvHv1ydut9X4QSb4NE94TH4KFgqXMAd6qACAqPahv5Mw-rEAEgRO&s=xZcvXYiegL2oQyez1hXAc7LztnIf0td72cHLhreveNw&e= .
>
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