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020 _a9783030145682
_9978-3-030-14568-2
024 7 _a10.1007/978-3-030-14568-2
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
_2thema
082 0 4 _a518.1
_223
100 1 _aSedighi, Art.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aFair Scheduling in High Performance Computing Environments
_h[electronic resource] /
_cby Art Sedighi, Milton Smith.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXI, 132 p. 77 illus., 74 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 1 Introduction 1 -- Chapter 2 Financial Market Risk 9 -- Chapter 3 Scheduling in High Performance Computing 24 -- Chapter 4 Fairshare Scheduling 33 -- Chapter 5 Multi-Criteria Scheduling: A Mathematical Model 43 -- Chapter 6 Simulation & Methodology 56 -- Chapter 7 DSIM 67 -- Chapter 8 Simulation Scenarios 73 -- Chapter 9 Overview of Results 90 -- Chapter 10 Class A Results and Analysis 101 -- Chapter 11 Class B Results and Analysis 118 -- Chapter 12 Class C Results and Analysis 139 -- Chapter 13 Class D Results and Simulations 153 -- Chapter 14 Conclusion 173. .
520 _aThis book introduces a new scheduler to fairly and efficiently distribute system resources to many users of varying usage patterns compete for them in large shared computing environments. The Rawlsian Fair scheduler developed for this effort is shown to boost performance while reducing delay in high performance computing workloads of certain types including the following four types examined in this book: i. Class A – similar but complementary workloads ii. Class B – similar but steady vs intermittent workloads iii. Class C – Large vs small workloads iv. Class D – Large vs noise-like workloads This new scheduler achieves short-term fairness for small timescale demanding rapid response to varying workloads and usage profiles. Rawlsian Fair scheduler is shown to consistently benefit workload Classes C and D while it only benefits Classes A and B workloads where they become disproportionate as the number of users increases. A simulation framework, dSim, simulates the new Rawlsian Fair scheduling mechanism. The dSim helps achieve instantaneous fairness in High Performance Computing environments, effective utilization of computing resources, and user satisfaction through the Rawlsian Fair scheduler.
650 0 _aAlgorithms.
650 0 _aComputer networks .
650 0 _aMicroprocessors.
650 0 _aComputer architecture.
650 1 4 _aAlgorithms.
650 2 4 _aComputer Communication Networks.
650 2 4 _aProcessor Architectures.
700 1 _aSmith, Milton.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030145675
776 0 8 _iPrinted edition:
_z9783030145699
776 0 8 _iPrinted edition:
_z9783030145705
856 4 0 _uhttps://doi.org/10.1007/978-3-030-14568-2
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c173878
_d173878