BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20211207T055413Z
LOCATION:242
DTSTART;TZID=America/Chicago:20211115T140000
DTEND;TZID=America/Chicago:20211115T143000
UID:submissions.supercomputing.org_SC21_sess340_ws_espm106@linklings.com
SUMMARY:Performance Evaluation of Python Parallel Programming Models: Char
 m4Py and Mpi4py
DESCRIPTION:Workshop\n\nPerformance Evaluation of Python Parallel Programm
 ing Models: Charm4Py and Mpi4py\n\nFink\n\nPython is rapidly becoming the 
 lingua franca of machine learning and scientific computing. With the broad
  use of frameworks such as Numpy, SciPy, and TensorFlow, scientific comput
 ing and machine learning are seeing a productivity boost on systems withou
 t a requisite loss in performance. While high-performance libraries often 
 provide adequate performance within a node, distributed computing is requi
 red to scale Python across nodes and make it truly competitive in large-sc
 ale high-performance computing. Many frameworks, such as Charm4Py, DaCe, D
 ask, Legate Numpy, mpi4py, and Ray, scale Python across nodes. However, li
 ttle is known about these frameworks' relative strengths and weaknesses, l
 eaving practitioners and scientists without enough information about which
  frameworks are suitable for their requirements. In this paper, we seek to
  narrow this knowledge gap by studying the relative performance of two suc
 h frameworks: Charm4Py and mpi4py.\n\nWe perform a comparative performanc
 e analysis of Charm4Py and mpi4py using CPU and GPU-based microbenchmarks,
  including TaskBench and other representative mini-apps for scientific com
 puting.\n\nTag: Architectures, Big Data, Cloud and Distributed Computing, 
 Extreme Scale Computing, Parallel Programming Languages and Models, Parall
 el Programming Systems, Quantum Computing, Scientific Computing, System So
 ftware and Runtime Systems\n\nRegistration Category: Workshop Reg Pass
END:VEVENT
END:VCALENDAR