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SUMMARY:AI Accelerators 101 - Daniel Kroening - AWS
DTSTART:20250521T110000Z
DTEND:20250521T120000Z
UID:TALK232453@talks.cam.ac.uk
CONTACT:Tobias Grosser
DESCRIPTION:LLMs are arguably among the largest technology investments \ns
 ince the moon landing\, and rely on custom hardware accelerators both for 
 training and inference. The talk will cover accelerating LLM transformer a
 rchitectures using the combination of a compiler and a systolic compute ar
 ray. The key enabler to achieving meaningful performance using the systoli
 c compute array are deep program analyses \nof the model architecture in t
 he Neuron Compiler. I will briefly report on our effort to build a verifie
 d (using Lean) compiler from XLA/HLO to the Trainium ISA.\n\n*Daniel Kroen
 ing* is a Senior Principal Applied Scientist at Amazon\, where he works on
  the correctness of the Neuron Compiler for distributed training and infer
 ence. Prior to joining Amazon\, he worked as a Professor of Computer Scien
 ce at the University of Oxford and is the co-founder of Diffblue Ltd.\, a 
 University spinout that develops AI that targets code and code-like artefa
 cts. He wrote the CBMC (for C)\, JBMC (for Java) and EBMC (for SystemVeril
 og) model checkers\; CBMC is the engine of Kani (for verifying unsafe Rust
 ). He has received the Semiconductor Research Corporation (SRC) Inventor R
 ecognition Award\, an IBM Faculty Award\, a Microsoft Research SEIF Award\
 , the Wolfson Research Merit Award\, and the Rance Cleaveland Test-of-Time
  tool award. He serves on the CAV steering committee and was co-chair of F
 LOC 2018\, EiC of Springer FMSD\, and is co-author of the textbooks on Dec
 ision Procedures and Model Checking.\n\n!https://upload.wikimedia.org/wiki
 pedia/commons/thumb/9/94/Pizza.svg/330px-Pizza.svg.png!\n\n*We will have P
 izza! Register such that we can get the right amount of food:*\n\n https:/
 /docs.google.com/forms/d/1RlUWlAroGtv-cePwe2lL118KbQFzTX647tn4zcmCbuA/view
 form?edit_requested=true
LOCATION:Computer Laboratory\, William Gates Building\, LT2
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