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Memory and Parallelism Analysis Using a Platform-Independent Approach (1904.08762v1)
Published 18 Apr 2019 in cs.DC, cs.AR, and cs.PF
Abstract: Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.