BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121115T203000Z
DTEND:20121115T210000Z
LOCATION:255-BC
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: The NAS Parallel Benchmarks (NPB) are a well-known suite of  benchmarks that proxy scientific computing applications.  They specify several problem sizes that represent how such applications may run on different sizes of HPC systems.  However, even the largest problem (Class F) is still far too small to exercise properly a Petascale supercomputer.  Our work shows how one may scale the Block Tridiagonal (BT) NPB from todays size to Petascale and Exascale computing systems.   In this paper we discuss the pros and cons of various ways of scaling.   We discuss how scaling BT would impact computation, memory access and communications, and highlight the expected bottleneck, which turns out to be not memory or communication bandwidth, but latency. Two complementary ways are presented to overcome latency obstacles. We also describe a practical method to gather approximate performance data for BT at exascale on actual hardware, without requiring an exascale system.
SUMMARY:Extending the BT NAS Parallel Benchmark to Exascale Computing
PRIORITY:3
END:VEVENT
END:VCALENDAR
BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121115T203000Z
DTEND:20121115T210000Z
LOCATION:255-BC
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: The NAS Parallel Benchmarks (NPB) are a well-known suite of  benchmarks that proxy scientific computing applications.  They specify several problem sizes that represent how such applications may run on different sizes of HPC systems.  However, even the largest problem (Class F) is still far too small to exercise properly a Petascale supercomputer.  Our work shows how one may scale the Block Tridiagonal (BT) NPB from todays size to Petascale and Exascale computing systems.   In this paper we discuss the pros and cons of various ways of scaling.   We discuss how scaling BT would impact computation, memory access and communications, and highlight the expected bottleneck, which turns out to be not memory or communication bandwidth, but latency. Two complementary ways are presented to overcome latency obstacles. We also describe a practical method to gather approximate performance data for BT at exascale on actual hardware, without requiring an exascale system.
SUMMARY:Extending the BT NAS Parallel Benchmark to Exascale Computing
PRIORITY:3
END:VEVENT
END:VCALENDAR