dc.contributor.author | Gupta, Raghav | |
dc.contributor.author | Kumar, Vivek (Advisor) | |
dc.date.accessioned | 2023-04-15T14:47:14Z | |
dc.date.available | 2023-04-15T14:47:14Z | |
dc.date.issued | 2022-05 | |
dc.identifier.uri | http://repository.iiitd.edu.in/xmlui/handle/123456789/1197 | |
dc.description.abstract | Future multi-core processors will be heterogeneous, be increasingly less reliable, and operate in dynamically changing operating conditions. Such environments will result in a constantly varying pool of hardware resources which can greatly complicate the task of efficiently exposing a program’s parallelism onto these resources. Coupled with this uncertainty is the diverse set of efficiency metrics that users may desire. In this paper we implement Fugu, a runtime library which dynamically, continuously, rapidly and transparently adapts a program’s parallelism, using the Argobots framework. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IIIT-Delhi | en_US |
dc.subject | Argobots | en_US |
dc.subject | run-time optimization | en_US |
dc.subject | performance tuning | en_US |
dc.subject | performance portability | en_US |
dc.subject | parallel programming | en_US |
dc.subject | Autotuning | en_US |
dc.title | Adaptive concurrency throttling in the exascale era | en_US |