Exploiting historical data: pruning autotuning spaces and estimating the number of tuning steps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F19%3A00115100" target="_blank" >RIV/00216224:14610/19:00115100 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-48340-1_23" target="_blank" >http://dx.doi.org/10.1007/978-3-030-48340-1_23</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-48340-1_23" target="_blank" >10.1007/978-3-030-48340-1_23</a>
Alternative languages
Result language
angličtina
Original language name
Exploiting historical data: pruning autotuning spaces and estimating the number of tuning steps
Original language description
Autotuning, the practice of automatic tuning of code to provide performance portability, has received increased attention in the research community, especially in high performance computing. Ensuring high performance on a variety of hardware usually means modifications to the code, often via different values of a selected set of parameters, such as tiling size, loop unrolling factor or data layout. However, the search space of all possible combinations of these parameters can be enormous. Traditional search methods often fail to find a well-performing set of parameter values quickly. We have found that certain properties of tuning spaces do not vary much when hardware is changed. In this paper, we demonstrate that it is possible to use historical data to reliably predict the number of tuning steps necessary to find a well-performing configuration, and to reduce the size of the tuning space. We evaluate our hypotheses on a number of GPU-accelerated benchmarks written in CUDA and OpenCL.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_013%2F0001802" target="_blank" >EF16_013/0001802: CERIT Scientific Cloud</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
9783030483395
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
13
Pages from-to
295-307
Publisher name
Springer, Cham
Place of publication
Cham, Switzerland
Event location
Göttingen
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000557422400001