Titlebook: Languages and Compilers for Parallel Computing; 27th International W James Brodman,Peng Tu Conference proceedings 2015 Springer Internation

FLING

Optimistic Parallelism on GPUsise to cross-iteration dependences. The execution of a speculatively parallelized loop consists of five phases: scheduling, computation, misspeculation check, result committing, and misspeculation recovery. While the first two phases enable exploitation of data parallelism, the latter three phases r

出处

昏睡中

GLES: A Practical GPGPU Optimizing Compiler Using Data Sharing and Thread Coarseningization methods are impractical for many applications that contain divergent control flows, and they failed to fully exploit optimization opportunities in data sharing and thread coarsening. In this paper, we present GLES, an optimizing compiler for GPGPU programs. GLES proposes two optimization tec

Reverie

Mri485

intertwine

Understanding Co-run Degradations on Integrated Heterogeneous Processorsnderstanding on the influence of co-runners on such systems. The previous studys on this topic are on simulators with limited settings..In this work, we conduct a comprehensive investigation of the performance of co-running jobs on integrated heterogeneous processors. The investigation produces a li

DEI

Simultaneous Inspection: Hiding the Overhead of Inspector-Executor Style Dynamic Parallelizationde) effects to analyze whether there are data dependences that would prevent parallel execution. Only if no such dependences are found, does the executor phase actually run the loop iterations in parallel. In previous works, the overhead of the inspection must either be amortized by the parallel exe

output

intention

Eulogy