Name
Abstract | ||
|---|---|---|
Since the demand for computing power increases, new architectures arise to obtain better performance. An important class of integrated devices is heterogeneous architectures, which join different specialized hardware into a single chip, composing a System on Chip - SoC. Within this context, effectively splitting tasks between the different architectures is primal to obtain efficiency and performance. In this work, we evaluate two heterogeneous architectures: one composed of a general-purpose CPU and a graphics processing unit (GPU) integrated into a single chip (AMD Kaveri SoC), and another composed by a general-purpose CPU and a Field Programmable Gate Array (FPGA) integrated into a single chip (Intel Arria 10 SoC). We investigate how data partitioning affects the performance of each device in a collaborative execution through the decomposition of the data domain. As a case study, we apply the technique in the well-known Lattice Boltzmann Method (LBM), analyzing the performance of five kernels in both architectures. Our experimental results show that non-uniform partitioning improves LBM kernels performance by up to 11.40% and 15.15% on AMD Kaveri and Intel Arria 10, respectively. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SBAC-PAD.2019.00031 | 2019 31st International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) |
Keywords | Field | DocType |
Heterogeneous Architectures,Collaborative Execution,Non-Uniform Partitioning,FPGA,GPU,Lattice Boltzmann Method | System on a chip,Data domain,Computer science,Parallel computing,Lattice Boltzmann methods,Field-programmable gate array,Chip,Integrated devices,Graphics processing unit,Data partitioning | Conference |
ISSN | ISBN | Citations |
1550-6533 | 978-1-7281-4195-4 | 0 |
PageRank | References | Authors |
0.34 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriel Freytag | 1 | 0 | 0.68 |
| Matheus da Silva Serpa | 2 | 2 | 2.73 |
| Joao Vicente Ferreira Lima | 3 | 0 | 0.34 |
| Paolo Rech | 4 | 155 | 23.92 |
| Philippe O. Navaux | 5 | 448 | 57.19 |