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TaskInsight: Understanding Task Schedules Effects on Memory and Performance
dc.contributor.author | Ceballos, Germán |
dc.contributor.author | Grass, Thomas |
dc.contributor.author | Hugo, Andra |
dc.contributor.author | Black-Schaffer, David |
dc.contributor.other | Barcelona Supercomputing Center |
dc.date.accessioned | 2017-02-20T14:25:24Z |
dc.date.available | 2017-02-20T14:25:24Z |
dc.date.issued | 2017-02 |
dc.identifier.citation | Ceballos, Germán [et al.]. TaskInsight: Understanding Task Schedules Effects on Memory and Performance. A: 8th International Workshop on Programming Models and Applications for Multicores and Manycores. "PMAM'17 Proceedings of the 8th International Workshop on Programming Models and Applications for Multicores and Manycores". New York: Association for Computing Machinery, 2017, p. 11-20. |
dc.identifier.uri | http://hdl.handle.net/2117/101245 |
dc.description.abstract | Recent scheduling heuristics for task-based applications have managed to improve their by taking into account memory-related properties such as data locality and cache sharing. However, there is still a general lack of tools that can provide insights into why, and where, different schedulers improve memory behavior, and how this is related to the applications' performance. To address this, we present TaskInsight, a technique to characterize the memory behavior of different task schedulers through the analysis of data reuse between tasks. TaskInsight provides high-level, quantitative information that can be correlated with tasks' performance variation over time to understand data reuse through the caches due to scheduling choices. TaskInsight is useful to diagnose and identify which scheduling decisions affected performance, when were they taken, and why the performance changed, both in single and multi-threaded executions. We demonstrate how TaskInsight can diagnose examples where poor scheduling caused over 10% difference in performance for tasks of the same type, due to changes in the tasks' data reuse through the private and shared caches, in single and multi-threaded executions of the same application. This flexible insight is key for optimization in many contexts, including data locality, throughput, memory footprint or even energy efficiency. |
dc.description.sponsorship | We thank the reviewers for their feedback. This work was supported by the Swedish Research Council, the Swedish Foundation for Strategic Research project FFL12-0051 and carried out within the Linnaeus Centre of Excellence UPMARC, Uppsala Programming for Multicore Architectures Research Center. This paper was also published with the support of the HiPEAC network that received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 687698. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.publisher | Association for Computing Machinery |
dc.subject | Àrees temàtiques de la UPC::Enginyeria elèctrica |
dc.subject.classification | Data mining |
dc.subject.lcsh | Memory management (Computer science) |
dc.subject.lcsh | Data mining |
dc.subject.other | Task-based scheduling |
dc.subject.other | Data Reuse |
dc.subject.other | Data Locality |
dc.title | TaskInsight: Understanding Task Schedules Effects on Memory and Performance |
dc.type | Conference report |
dc.subject.lemac | Gestió de memòria (Informàtica) |
dc.subject.lemac | Dades--Recuperació (Informàtica) |
dc.identifier.doi | 10.1145/3026937.3026943 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://dl.acm.org/citation.cfm?id=3026943&CFID=902594512&CFTOKEN=40711044 |
dc.rights.access | Open Access |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/687698/EU/High Performance and Embedded Architecture and Compilation/HiPEAC |
local.citation.contributor | 8th International Workshop on Programming Models and Applications for Multicores and Manycores |
local.citation.pubplace | New York |
local.citation.publicationName | PMAM'17 Proceedings of the 8th International Workshop on Programming Models and Applications for Multicores and Manycores |
local.citation.startingPage | 11 |
local.citation.endingPage | 20 |