Communications of the ACM
A domain-specific approach to heterogeneous parallelism
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming
Insulating the scientific programmer from perilous parallel architecture
Proceedings of the 9th Workshop on Parallel/High-Performance Object-Oriented Scientific Computing
Raising the level of abstraction for developing message passing applications
The Journal of Supercomputing
Which problems does a multi-language virtual machine need to solve in the multicore/manycore era?
Proceedings of the compilation of the co-located workshops on DSM'11, TMC'11, AGERE!'11, AOOPES'11, NEAT'11, & VMIL'11
A new smartphone lane detection system: realizing true potential of multi-core mobile devices
Proceedings of the 4th Workshop on Mobile Video
Introducing 'Bones': a parallelizing source-to-source compiler based on algorithmic skeletons
Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units
Proceedings of the 9th conference on Computing Frontiers
Auto-generation and auto-tuning of 3D stencil codes on GPU clusters
Proceedings of the Tenth International Symposium on Code Generation and Optimization
PQL: a purely-declarative java extension for parallel programming
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
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The ParLab at Berkeley, UPCRC-Illinois, and the Pervasive Parallel Laboratory at Stanford are studying how to make parallel programming succeed given industry's recent shift to multicore computing. All three centers assume that future microprocessors will have hundreds of cores and are working on applications, programming environments, and architectures that will meet this challenge. This article briefly surveys the similarities and difference in their research.