Computer generation of efficient software viterbi decoders

HIGH PERFORMANCE EMBEDDED ARCHITECTURES AND COMPILERS, PROCEEDINGS(2010)

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Abstract
This paper presents a program generator for fast software Viterbi decoders for arbitrary convolutional codes. The input to the generator is a specification of the code and a single-instruction multiple-data (SIMD) vector length. The output is an optimized C implementation of the decoder that uses explicit Intel SSE vector instructions. At the heart of the generator is a small domain-specific language called VL to express the structure of the forward pass. Vectorization is done by rewriting VL expressions, which a compiler then translates into actual code in addition to performing further optimizations specific to the vector instruction set. Benchmarks show that the generated decoders match the performance of available expert hand-tuned implementations, while spanning the entire space of convolutional codes. An online interface to the generator is provided at www.spiral.net.
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Key words
vector instruction set,arbitrary convolutional code,computer generation,convolutional code,vl expression,explicit intel sse vector,efficient software viterbi decoder,vector length,entire space,actual code,program generator,available expert,vectorization,viterbi decoder,single instruction multiple data,viterbi algorithm,domain specific language
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