EXA2PRO: A Framework for High Development Productivity on Heterogeneous Computing Systems
Creators
- 1. Department of Electrical and Computer Engineering, National Technical University of Athens, Greece
- 2. Dept. of Computer and Information Science, Linköping University, Linköping, Sweden
- 3. Chemical Process and Energy Resources Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
- 4. Maison de la Simulation, CEA, CNRS, France
- 5. Université de Pau et des Pays de l'Adour, Pau, France
- 6. Bordeaux University, Bordeaux, France
- 7. Information Tech- nologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
Description
Programming upcoming exascale computing sys-
tems is expected to be a major challenge. New programming
models are required to improve programmability, by hiding the
complexity of these systems from application developers. The
EXA2PRO programming framework aims at improving devel-
opers’ productivity for applications that target heterogeneous
computing systems. It is based on advanced programming models
and abstractions that encapsulate low-level platform-specific
optimizations and it is supported by a runtime that handles
application deployment on heterogeneous nodes. It supports a
wide variety of platforms and accelerators (CPU, GPU, FPGA-
based Data-Flow Engines), allowing developers to efficiently
exploit heterogeneous computing systems, thus enabling more
HPC applications to reach exascale computing. The EXA2PRO
framework was evaluated using four HPC applications from
different domains. By applying the EXA2PRO framework, the
applications were automatically deployed and evaluated on a
variety of computing architectures, enabling developers to obtain
performance results on accelerators, test scalability on MPI
clusters and productively investigate the degree by which each
application can efficiently use different types of hardware re-
sources.
Files
EXA2PRO___TPDS.pdf
Files
(5.2 MB)
Name | Size | Download all |
---|---|---|
md5:c0d2cbec21828e58fef9c2eab82fb177
|
5.2 MB | Preview Download |