Name
Title | ||
|---|---|---|
Towards Memory-Load Balanced Fast Fourier Transformations in Fine-Grain Execution Models |
Abstract | ||
|---|---|---|
The code let model is a fine-grain dataflow-inspired program execution model that balances the parallelism and overhead of the runtime system. It plays an important role in terms of performance, scalability, and energy efficiency in exascale studies such as the DARPA UHPC project and the DOE X-Stack project. As an important application, the Fast Fourier Transform (FFT) has been deeply studied in fine-grain models, including the code let model. However, the existing work focuses on how fine-grain models achieve more balanced workload comparing to traditional coarse-grain models. In this paper, we make an important observation that the flexibility of execution order of tasks in fine-grain models improves utilization of memory bandwidth as well. We use the code let model and the FFT application as a case study to show that a proper execution order of tasks (or code lets) can significantly reduce memory contention and thus improve performance. We propose an algorithm that provides a heuristic guidance of the execution order of the code lets to reduce memory contention. We implemented our algorithm on the IBM Cyclops-64 architecture. Experimental results show that our algorithm improves up to 46% performance compared to a state-of-the-art coarse-grain implementation of the FFT application on Cyclops-64. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IPDPSW.2013.47 | IPDPS Workshops |
Keywords | Field | DocType |
towards memory-load balanced fast,important role,traditional coarse-grain model,fine-grain execution models,execution order,fine-grain model,important observation,important application,fourier transformations,proper execution order,memory contention,fft application,fine-grain dataflow-inspired program execution,fast fourier transforms,resource allocation,synchronization,memory management,instruction sets,computational modeling,fft,memory bandwidth | Heuristic,Interleaved memory,Memory bandwidth,Computer science,Load balancing (computing),Parallel computing,Fast Fourier transform,Execution model,Runtime system,Scalability | Conference |
Citations | PageRank | References |
0 | 0.34 | 29 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Chen | 1 | 232 | 77.45 |
| Yao Wu | 2 | 34 | 12.69 |
| Stéphane Zuckerman | 3 | 42 | 8.16 |
| Guang R. Gao | 4 | 2661 | 265.87 |