BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260422T143039Z
LOCATION:Exhibit Hall A3
DTSTART;TZID=America/New_York:20241120T083000
DTEND;TZID=America/New_York:20241120T100000
UID:submissions.supercomputing.org_SC24_sess501@linklings.com
SUMMARY:ACM and IEEE-CS Award Presentations
DESCRIPTION:High Level Compiler Transformations: Brief History and Applica
 tions (2024 ACM/IEEE-CS Ken Kennedy Award presentation)\n\nHigh-level comp
 iler transformations were developed soon after the first compilers. They a
 re used to manipulate compound statements such as loops and if statements 
 in order to vectorize, parallelize, and tile them to benefit from parallel
 ism and enhance locality.  Since high-level compiler transforma...\n\n\nDa
 vid Padua (University of Illinois Urbana-Champaign)\n---------------------
 \nImmense-Scale Machine Learning: The Big, the Small, and the Not Right at
  All (2024 IEEE-CS Seymour Cray Computer Engineering Award)\n\nWe start wi
 th key aspects of the decade-long evolution of Google’s Tensor Processing 
 Systems.  These systems have unique requirements arising from serving bill
 ions of daily users across multiple products in production environments.  
 Training Large Language ML Models (LLMs) can require 100,000 ...\n\n\nNorm
  Jouppi (Google)\n---------------------\nValidated AI-Powered Machine Lear
 ning for Accelerating Delivery of Scientific Grand Challenges (2024 IEEE-C
 S Sidney Fernbach Award)\n\nA US imperative is to deliver a Fusion Pilot P
 lant to accelerate the fusion energy development timeline.  This will rely
  heavily on validated scientific and engineering advances driven by HPC to
 gether with advanced statistical methods featuring artificial intelligence
 /deep learning/machine learning ...\n\n\nWilliam Tang (Princeton Plasma Ph
 ysics Laboratory)\n\nRegistration Category: Tech Program Reg Pass\n\nSessi
 on Chairs: Venkatesh Kannan (Irish Centre for High‑End Computing (ICHEC)) 
 and Scott Pakin (Los Alamos National Laboratory (LANL))
END:VEVENT
END:VCALENDAR
