%0 Report %T PaSTeL : Parallel Runtime and Algorithms for Small Datasets %+ Laboratoire d'Informatique de Grenoble (LIG) %+ Middleware efficiently scalable (MESCAL) %A Videau, Brice %A Saule, Erik %A Méhaut, Jean-François %N RR-6650 %P 20 %I INRIA %8 2008 %D 2008 %K multi-core architecture %K small datasets %K STL %K performance study %K programming %Z Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]Reports %X In this document, we put forward PaSTeL, an engine dedicated to parallel algorithms. PaSTeL offers both a programming model, to build parallel algorithms and an execution model based on work-stealing. Special care has been taken on using optimized thread activation and synchronization mechanisms. In order to illustrate the use of PaSTeL a subset of the STL's algorithms was implemented, which were also used on performance experiments. PaSTeL's performance is evaluated on a laptop computer using two cores, but also on a 16 cores platform. PaSTeL shows better performance than other implementations of the STL, especially on small datasets. %G English %2 https://inria.hal.science/inria-00322158v2/document %2 https://inria.hal.science/inria-00322158v2/file/RR-6650.pdf %L inria-00322158 %U https://inria.hal.science/inria-00322158 %~ UGA %~ CNRS %~ INRIA %~ UNIV-GRENOBLE1 %~ UNIV-PMF_GRENOBLE %~ INPG %~ INRIA-RHA %~ INRIA-RRRT %~ LIG %~ INRIA_TEST %~ TESTALAIN1 %~ INRIA2 %~ LARA %~ INRIA-RENGRE %~ POLYTECH-GRENOBLE %~ LIG_SIDCH