[Crib-list] Fwd: VIRTUAL "CRIBB Seminar" -- Spk. Dr. Johannes Feldman - Friday, May 5, 2023 @ 12:00 Noon - 1:00 PM

[Shirley Entzminger]

   VIRTUAL...

         COMPUTATIONAL RESEARCH in BOSTON and BEYOND SEMINAR
                             (CRIBB)


   ZOOM meeting info...

                    https://mit.zoom.us/j/96155042770

                    Meeting ID: 961 5504 2770

====================================

DATE:	Friday, May 5, 2023

TIME:	12:00 PM - 1:00 PM


SPEAKER:  DR. JOHANNES FELDMANN  (Co-Founder and CTO at Salience Labs, 
Oxford, UK.)


TITLE:    Ultra-low latency energy saving computing with silicon 
photonics


ABSTRACT:

Silicon photonics (SiPh) achieves ultra-low latency processing and data 
movement and promises qualitative improvement in energy efficiency. We 
review existing SiPh technology, benefits, and remaining challenges. 
SiPh removes the gap in data communication between fiber-optical 
macro-level connectivity and the present electronic digital-based data 
movement at the system down to the chip level. SiPh also rejuvenates 
optical and electrical analog computing taking advantage of low-cost 
mass manufacturing of SiPh chips and their packaging with traditional 
electronic digital components, e.g., an amplitude-based modulation 
allows for a chip that clocks at 10’s of GHz.

Matrix multiplication (MatMul) is the key compute operation in AI 
inference, signal processing, optimal control, numerical modelling, and 
other matrix-math heavy compute workloads. A hybrid electronic/SiPh chip 
can achieve orders of magnitude performance improvement in low precision 
MatMul, e.g., delivers a 60x reduction in latency for full AI inference 
workloads in our simulation and can be mass-manufactured at 
production-level foundries. Effective algorithmic/architecture co-design 
requires a better understanding of applications that can take advantage 
of reduced latency and benefit from low energy consumption. We are open 
for collaborations with potential customers in need for customized 
chips.

References:

1. Parallel convolutional processing using an integrated photonic tensor 
core. Nature, 2021.
2. All-optical spiking neurosynaptic networks with self-learning 
capabilities. Nature, 2019.

=======================================

For information about the "Computational Research in Boston and Beyond 
Seminar"
CRIBB), please visit:

               https://math.mit.edu/sites/crib/


=================

Shirley A. Entzminger
Administrative Assistant II
Department of Mathematics
Massachusetts Institute of Technology
77 Massachusetts Avenue
Building 2, Room 350A
Cambridge, MA 02139
PHONE: 	(617) 253-4994
E-mail:	daisymae at math.mit.edu
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