BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Denver
X-LIC-LOCATION:America/Denver
BEGIN:DAYLIGHT
TZOFFSETFROM:-0700
TZOFFSETTO:-0600
TZNAME:MDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0600
TZOFFSETTO:-0700
TZNAME:MST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20240116T191700Z
LOCATION:405-406-407
DTSTART;TZID=America/Denver:20231115T163000
DTEND;TZID=America/Denver:20231115T170000
UID:submissions.supercomputing.org_SC23_sess183_pap263@linklings.com
SUMMARY:SYnergy: Fine-Grained Energy-Efficient Heterogeneous Computing for
  Scalable Energy Saving
DESCRIPTION:Paper\n\nKaijie Fan (TU Berlin, University of Salerno); Marco 
 D'Antonio, Lorenzo Carpentieri, and Biagio Cosenza (University of Salerno)
 ; and Federico Ficarelli and Daniele Cesarini (CINECA)\n\nEnergy-efficient
  computing uses power management techniques such as frequency scaling to s
 ave energy. Implementing energy-efficient techniques on large-scale comput
 ing systems is challenging. While most modern architectures, including GPU
 s, are capable of frequency scaling, these features are often not availabl
 e on large systems.  \n\nWe propose SYnergy, a novel energy-efficient appr
 oach that spans languages, compilers, runtimes, and job schedulers to achi
 eve unprecedented fine-grained energy savings on large-scale heterogeneous
  clusters. SYnergy defines an extension to the SYCL programming model that
  allows programmers to define a specific energy goal for each kernel.  Thr
 ough compiler integration and a machine learning model, each kernel is sta
 tically optimized for the specific target. The methodology is inherently p
 ortable and has been evaluated on both NVIDIA and AMD GPUs. Experimental r
 esults show unprecedented improvements in energy and energy-related metric
 s on real-world applications, as well as scalable energy savings on a 64-G
 PU cluster.\n\nTag: Cloud Computing, Distributed Computing, Energy Efficie
 ncy, Performance Measurement, Modeling, and Tools\n\nRegistration Category
 : Tech Program Reg Pass\n\nReproducibility Badges: Artifact Available, Art
 ifact Functional, Results Reproduced\n\nSession Chair: Radu Prodan (Univer
 sity of Klagenfurt, Austria)
END:VEVENT
END:VCALENDAR