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Numerical computations have accelerated significantly since 2005 thanks to two complementary, silicon-enabled trends: multi-core processing and single instruction, multiple data (SIMD) accelerators. Unfortunately, due to fundamental limitations of physics, these two trends could not be accompanied by a corresponding increase in memory, storage, and I/O bandwidth. We describe Application Acceleration...
This paper examines whether lossy compression can be used effectively in physics simulations as a possible strategy to combat the expected data-movement bottleneck in future high performance computing architectures. We show that, for the codes and simulations we tested, compression levels of 3–5X can be applied without causing significant changes to important physical quantities. Rather than applying...
Over the course of the last 20 years, compression has evolved from a somewhat esoteric domain of mathematics and computer science into a ubiquitous consumer electronics technology. Given the prevalence and success of speech, audio, image, and video compression algorithms in consumer electronics, it is surprising that many high-speed digital signal processing (DSP) systems such as wireless infrastructure,...
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