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DTSTART:19700308T020000
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DTSTAMP:20210402T160554Z
LOCATION:Track 2
DTSTART;TZID=America/New_York:20201112T111000
DTEND;TZID=America/New_York:20201112T113000
UID:submissions.supercomputing.org_SC20_sess208_ws_pmbss104@linklings.com
SUMMARY:Benchmarking Julia’s Communication Performance: Is Julia HPC Ready
  or Full HPC?
DESCRIPTION:Workshop\n\nBenchmarking Julia’s Communication Performance: Is
  Julia HPC Ready or Full HPC?\n\nHunold, Steiner\n\nJulia has quickly beco
 me one of the main programming languages for computational sciences, mainl
 y due to its speed and flexibility. The speed and efficiency of Julia are 
 the main reasons why researchers in the field of High Performance Computin
 g have started porting their applications to Julia.\n\nSince Julia has a v
 ery small binding-overhead to C, many efficient computational kernels can 
 be integrated into Julia without any noticeable performance drop. For that
  reason, highly tuned libraries, such as the Intel MKL or OpenBLAS, will a
 llow Julia applications to achieve similar computational performance as th
 eir C counterparts. Yet, two questions remain: 1) How fast is Julia for me
 mory-bound applications? 2) How efficient can MPI functions be called from
  a Julia application?\n\nIn this paper, we will assess the performance of 
 Julia with respect to HPC. To that end, we examine the raw throughput achi
 evable with Julia using a new Julia port of the well-known STREAM benchmar
 k. We also compare the running times of the most commonly used MPI collect
 ive operations (e.g., MPI_Allreduce) with their C counterparts. Our analys
 is shows that HPC performance of Julia is on-par with C in the majority of
  cases.\n\nRegistration Category: Workshop Reg Pass
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