Can Traditional Programming Bridge the Ninja Performance Gap for Parallel Computing Applications?

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Provided by: Intel
Topic: Hardware
Format: PDF
Current processor trends of integrating more cores with wider SIMD units, along with a deeper and complex memory hierarchy, have made it increasingly more challenging to extract performance from applications. It is believed by some that traditional approaches to programming do not apply to these modern processors and hence radical new languages must be discovered. In this paper, the authors question this thinking and offer evidence in support of traditional programming methods and the performance-vs-programming effort effectiveness of common multi-core processors and upcoming manycore architectures in delivering significant speedup, and close-to-optimal performance for commonly used parallel computing workloads.
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