9:19 a.m.
SPCL_Bcast Virginia Smith
The Scalable Parallel Computing Lab's *SPCL_Bcast* seminar continues
with *Marian Verhelst of KU Leuven* presenting on *Heterogeneous
multi-core systems for efficient EdgeML*. Everyone is welcome to attend
(over Zoom)!
When: Thursday, 26th October, 9AM CET
Where: Zoom
Join <https://spcl.inf.ethz.ch/Bcast/join>
Abstract: Embedded ML applications are characterized by increasingly
diverse workloads, forming a rich mixture of signal processing, GeMM and
conv kernels, attention layers, and even graph processing. Accelerator
efficiency suffers from supporting this wide variety of kernels.
Heterogeneous multicore systems can offer a solution but come with their
own challenges, such as: 1.) How to find the most optimal combination of
cores?; 2.) How to efficiently map workloads across cores?; 3.) How to
share data between these cores? This talk will report on a heterogeneous
multi-core system for embedded neural network processing taped out at
KULeuven MICAS. Moreover, it will give an outlook on work in progress
towards further expanding this system for covering more workloads and
more heterogeneous cores.
Biography: Marian Verhelst is a full professor at the MICAS laboratories
of KU Leuven and a research director at imec. Her research focuses on
embedded machine learning, hardware accelerators, HW-algorithm co-design
and low-power edge processing. She received a PhD from KU Leuven in
2008, and worked as a research scientist at Intel Labs, Hillsboro OR
from 2008 till 2010. Marian is a member of the board of directors of
tinyML and active in the TPC’s of DATE, ISSCC, VLSI and ESSCIRC and was
the chair of tinyML2021 and TPC co-chair of AICAS2020. Marian is an IEEE
SSCS Distinguished Lecturer, was a member of the Young Academy of
Belgium, an associate editor for TVLSI, TCAS-II and JSSC and a member of
the STEM advisory committee to the Flemish Government. Marian received
the laureate prize of the Royal Academy of Belgium in 2016, the 2021
Intel Outstanding Researcher Award, the André Mischke YAE Prize for
Science and Policy in 2021, and two ERC grants.
More details & future talks <https://spcl.inf.ethz.ch/Bcast/>
Scalable Parallel Computing Lab (SPCL)
Department of Computer Science, ETH Zurich
Website <https://spcl.inf.ethz.ch> X(Twitter)
<https://twitter.com/spcl_eth> YouTube <https://www.youtube.com/@spcl>
GitHub <https://github.com/spcl>
