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VLSISP
2008

Memory-constrained Block Processing for DSP Software Optimization

8 years 10 months ago
Memory-constrained Block Processing for DSP Software Optimization
Digital signal processing (DSP) applications involve processing long streams of input data. It is important to take into account this form of processing when implementing embedded software for DSP systems. Task-level vectorization, or block processing, is a useful dataflow graph transformation that can significantly improve execution performance by allowing subsequences of data items to be processed through individual task invocations. In this way, several benefits can be obtained, including reduced context switch overhead, increased memory locality, improved utilization of processor pipelines, and use of more efficient DSP oriented addressing modes. On the other hand, block processing generally results in increased memory requirements since it effectively increases the sizes of the input and output values associated with processing tasks. In this paper, we investigate the memory-performance trade-off associated with block processing. We develop novel block processing algorithms that c...
Ming-Yung Ko, Chung-Ching Shen, Shuvra S. Bhattach
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2008
Where VLSISP
Authors Ming-Yung Ko, Chung-Ching Shen, Shuvra S. Bhattacharyya
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