Name
Abstract | ||
|---|---|---|
The graphics processor unit (GPU) is able to provide a low-cost and flexible software-based multi-core architecture for high performance computing. However, it is still very challenging to efficiently map the real-world applications to GPU and fully utilize the computational power of GPU. As a case study, we present a GPU-based implementation of a real-world digital signal processing (DSP) application: low-density parity-check (LDPC) decoder. The paper shows the efforts we made to map the algorithm onto the massively parallel architecture of GPU and fully utilize GPU's computational resources to significantly boost the performance. Moreover, several efficient data structures have been proposed to reduce the memory access latency and the memory bandwidth requirement. Experimental results show that the proposed GPU-based LDPC decoding accelerator can take advantage of the multi-core computational power provided by GPU and achieve high throughput up to 100.3Mbps. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/SASP.2011.5941084 | SASP |
Keywords | Field | DocType |
high throughput,graphics processor unit,flexible software-based multi-core architecture,memory bandwidth requirement,ldpc decoder,signal processing,computer graphic equipment,gpu,software based multicore architecture,data structures,massively parallel implementation,low density parity check decoder,cuda,multiprocessing systems,high performance computing,qc-ldpc decoder,computational resource,multi-core computational power,digital signal processing application,computational power,memory access latency,coprocessors,parallel implementation,parallel computing,parity check codes,gpu-based ldpc decoding accelerator,decoding,gpu-based implementation,instruction sets,parallel computer,throughput | Memory bandwidth,Supercomputer,Instruction set,Low-density parity-check code,Massively parallel,CUDA,Computer science,Parallel computing,Coprocessor,Graphics processing unit | Conference |
ISBN | Citations | PageRank |
978-1-4577-1212-8 | 26 | 1.46 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guohui Wang | 1 | 1088 | 60.78 |
| Michael Wu | 2 | 271 | 18.30 |
| Yang Sun | 3 | 378 | 24.59 |
| Joseph R. Cavallaro | 4 | 1175 | 115.35 |