Overview Statistic: PDF-Downloads (blue) and Frontdoor-Views (gray)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 4 of 4
Back to Result List

KART - A Runtime Compilation Library for Improving HPC Application Performance

  • The effectiveness of ahead-of-time compiler optimization heavily depends on the amount of available information at compile time. Input-specific information that is only available at runtime cannot be used, although it often determines loop counts, branching predicates and paths, as well as memory-access patterns. It can also be crucial for generating efficient SIMD-vectorized code. This is especially relevant for the many-core architectures paving the way to exascale computing, which are more sensitive to code-optimization. We explore the design-space for using input-specific information at compile-time and present KART, a C++ library solution that allows developers tocompile, link, and execute code (e.g., C, C++ , Fortran) at application runtime. Besides mere runtime compilation of performance-critical code, KART can be used to instantiate the same code multiple times using different inputs, compilers, and options. Other techniques like auto-tuning and code-generation can be integrated into a KART-enabled application instead of being scripted around it. We evaluate runtimes and compilation costs for different synthetic kernels, and show the effectiveness for two real-world applications, HEOM and a WSM6 proxy.
Metadaten
Author:Matthias NoackORCiD, Florian WendeORCiD, Georg Zitzlsberger, Michael Klemm, Thomas Steinke
Document Type:Book chapter
Parent Title (English):High Performance Computing: ISC High Performance 2017 International Workshops, DRBSD, ExaComm, HCPM, HPC-IODC, IWOPH, IXPUG, P^3MA, VHPC, Visualization at Scale, WOPSSS, Frankfurt, Germany, June 18-22, 2017, Revised Selected Papers
Volume:10524
First Page:389
Last Page:403
Series:LNCS
Publisher:Springer International Publishing
Year of first publication:2017
Notes:
Best Paper Award
Preprint:urn:nbn:de:0297-zib-60730
DOI:https://doi.org/10.1007/978-3-319-67630-2_29
Accept ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.