Title
Multiple Target Task Sharing Support for the OpenMP Accelerator Model.
Abstract
The use of GPU accelerators is becoming common in HPC platforms due to the their effective performance and energy efficiency. In addition, new generations of multicore processors are being designed with wider vector units and/or larger hardware thread counts, also contributing to the peak performance of the whole system. Although current directive-based paradigms, such as OpenMP or OpenACC, support both accelerators and multicore-based hosts, they do not provide an effective and efficient way to concurrently use them, usually resulting in accelerated programs in which the potential computational performance of the host is not exploited. In this paper we propose an extension to the OpenMP 4.5 directive-based programming model to support the specification and execution of multiple instances of task regions on different devices (i.e. accelerators in conjunction with the vector and heavily multi-threaded capabilities in multicore processors). The compiler is responsible for the generation of device-specific code for each device kind, delegating to the runtime system the dynamic schedule of the tasks to the available devices. The new proposed clause conveys useful insight to guide the scheduler while keeping a clean, abstract and machine independent programmer interface. The potential of the proposal is analyzed in a prototype implementation in the OmpSs compiler and runtime infrastructure. Performance evaluation is done using three kernels (N-Body, tiled matrix multiply and Stream) on different GPU-capable systems based on ARM, Intel x86 and IBM Power8. From the evaluation we observe speed-ups in the 8-20% range compared to versions in which only the GPU is used, reaching 96% of the additional peak performance thanks to the reduction of data transfers and the benefits introduced by the OmpSs NUMA-aware scheduler.
Year
DOI
Venue
2016
10.1007/978-3-319-45550-1_19
Lecture Notes in Computer Science
Field
DocType
Volume
x86,Programmer,Programming paradigm,Computer science,Parallel computing,Thread (computing),POWER8,Compiler,Multi-core processor,Operating system,Runtime system
Conference
9903
ISSN
Citations 
PageRank 
0302-9743
2
0.37
References 
Authors
4
5
Name
Order
Citations
PageRank
Guray Ozen141.27
Sergi Mateo284.99
Eduard Ayguadé32406216.00
Jesús Labarta41862165.09
James C. Beyer5394.99