Most of today’s mixed criticality platforms feature Systems on Chip (SoC) where a multi-core CPU complex (the host) competes with an integrated Graphic Processor Unit (iGPU, the device) for accessing central memory. The multi-core host and the iGPU share the same memory controller, which has to arbitrate data access to both clients through often undisclosed or non-priority driven mechanisms. Such aspect becomes critical when the iGPU is a high performance massively parallel computing complex potentially able to saturate the available DRAM bandwidth of the considered SoC. The contribution of this paper is to qualitatively analyze and characterize the conflicts due to parallel accesses to main memory by both CPU cores and iGPU, so to motivate the need of novel paradigms for memory centric scheduling mechanisms. We analyzed different well known and commercially available platforms in order to estimate variations in throughput and latencies within various memory access patterns, both at host and device side.

Memory interference characterization between CPU cores and integrated GPUs in mixed-criticality platforms / Cavicchioli, R.; Capodieci, N.; Bertogna, M.. - (2017), pp. 1-10. (Intervento presentato al convegno 22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017 tenutosi a cyp nel 2017) [10.1109/ETFA.2017.8247615].

Memory interference characterization between CPU cores and integrated GPUs in mixed-criticality platforms

Cavicchioli R.;Capodieci N.;Bertogna M.
2017

Abstract

Most of today’s mixed criticality platforms feature Systems on Chip (SoC) where a multi-core CPU complex (the host) competes with an integrated Graphic Processor Unit (iGPU, the device) for accessing central memory. The multi-core host and the iGPU share the same memory controller, which has to arbitrate data access to both clients through often undisclosed or non-priority driven mechanisms. Such aspect becomes critical when the iGPU is a high performance massively parallel computing complex potentially able to saturate the available DRAM bandwidth of the considered SoC. The contribution of this paper is to qualitatively analyze and characterize the conflicts due to parallel accesses to main memory by both CPU cores and iGPU, so to motivate the need of novel paradigms for memory centric scheduling mechanisms. We analyzed different well known and commercially available platforms in order to estimate variations in throughput and latencies within various memory access patterns, both at host and device side.
2017
2017
22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017
cyp
2017
1
10
Cavicchioli, R.; Capodieci, N.; Bertogna, M.
Memory interference characterization between CPU cores and integrated GPUs in mixed-criticality platforms / Cavicchioli, R.; Capodieci, N.; Bertogna, M.. - (2017), pp. 1-10. (Intervento presentato al convegno 22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017 tenutosi a cyp nel 2017) [10.1109/ETFA.2017.8247615].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1182137
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