High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications
Creators
- 1. Dalvan
- 2. Renato B.
- 3. Junior
- 4. Marco
- 5. Luiz Gustavo
Description
The stream processing domain is present in several real-world applications that are running on multi-core systems. In this paper, we focus on data compression applications that are an important sub-set of this domain. Our main goal is to assess the programmability and efficiency of domain-specific language called SPar. It was specially designed for expressing stream parallelism and it promises higher-level parallelism abstractions without significant performance losses. Therefore, we parallelized Lzip and Bzip2 compressors
with SPar and compared with state-of-the-art frameworks. The results revealed that SPar is able to efficiently exploit stream parallelism as well as provide suitable abstractions with less code intrusion and code re-factoring.
Files
data.zip
Files
(3.8 MB)
Name | Size | Download all |
---|---|---|
md5:bb0d4348a6922d50d9bcf4547a86780e
|
3.8 MB | Preview Download |