Projects per year
Near-memory Computing (NMC) promises improved performance for the applications that can exploit the features of emerging memory technologies such as 3D-stacked memory. However, it is not trivial to find such applications and specialized tools are needed to identify them. In this paper, we present PISA-NMC, which extends a state-of-the-art hardware agnostic profiling tool with metrics concerning memory and parallelism, which are relevant for NMC. The metrics include memory entropy, spatial locality, data-level, and basic-block-level parallelism. By profiling a set of representative applications and correlating the metrics with the application's performance on a simulated NMC system, we verify the importance of those metrics. Finally, we demonstrate which metrics are useful in identifying applications suitable for NMC architectures.
|Title of host publication||Proceedings of the 22nd Euromicro Conference on Digital System Design|
|Editors||Nikos Konofaos, Paris Kitsos|
|Place of Publication||Piscataway|
|Publisher||Institute of Electrical and Electronics Engineers|
|Number of pages||4|
|Publication status||Published - 24 Jun 2019|
|Event||22nd Euromicro Conference on Digital System Design, DSD 2019 - Kallithea, Kallithea, Chalkidiki, Greece|
Duration: 28 Aug 2019 → 30 Aug 2019
Conference number: 22
|Conference||22nd Euromicro Conference on Digital System Design, DSD 2019|
|Abbreviated title||DSD 2019|
|Period||28/08/19 → 30/08/19|
- Memory Entropy
- Spatial Locality
- Data-Level Parallelism
FingerprintDive into the research topics of 'Platform independent software analysis for near memory computing'. Together they form a unique fingerprint.
- 1 Finished
Corporaal, H., van Dalfsen, J., Singh, G., Chelini, L., Corda, S., Stuijk, S., Sanchez, V., Jordans, R., van der Hagen, D. & de Mol-Regels, M.
1/04/16 → 30/09/20
Project: Research direct