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作 者:Juan FANG Sheng LIN Huijing YANG Yixiang XU Xing SU
机构地区:[1]SU Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China
出 处:《Frontiers of Information Technology & Electronic Engineering》2023年第7期994-1006,共13页信息与电子工程前沿(英文版)
基 金:Project supported by the National Natural Science Foundation of China(Nos.62276011 and 61202076);the Natural Science Foundation of Beijing,China(No.4192007)。
摘 要:When multiple central processing unit(CPU)cores and integrated graphics processing units(GPUs)share off-chip main memory,CPU and GPU applications compete for the critical memory resource.This causes serious resource competition and has a negative impact on the overall performance of the system.We describe the competition for shared-memory resources in a CPU-GPU heterogeneous multi-core architecture,and a sharedmemory request scheduling strategy based on perceptual and predictive batch-processing is proposed.By sensing the CPU and GPU memory request conditions in the request buffer,the proposed scheduling strategy estimates the GPU latency tolerance and reduces mutual interference between CPU and GPU by processing CPU or GPU memory requests in batches.According to the simulation results,the scheduling strategy improves CPU performance by8.53%and reduces mutual interference by 10.38%with low hardware complexity.
关 键 词:CPU-GPU heterogeneous MULTI-CORE Unified memory Access scheduling
分 类 号:TP332[自动化与计算机技术—计算机系统结构]
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