Vectorization has been an important method of using data-level parallelism to accelerate scientific workloads on vector machines such as Cray for the past three decades. In the last decade it has also proven useful for accelerating multi-media and ...
Developers often rely on automatic vectorization to speed up fine-grained data-parallel code. However, for loop nests where the loops are shorter than the processor's SIMD width, automatic vectorization performs poorly. Vectorizers attempt to vectorize ...
Most high-performance microprocessors come equipped with general-purpose Single Instruction Multiple Data (SIMD) execution engines to enhance performance. Compilers use auto-vectorization techniques to identify vector parallelism and generate SIMD code ...
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