Computational accelerators, such as manycore NVIDIA GPUs, Intel Xeon Phi and FPGAs, are becoming common in workstations, servers and supercomputers for scientific and engineering...
Yonghong Yan 0001, Pei-Hung Lin, Chunhua Liao, Bro...
Modern graphics processing units (GPUs) include hardwarecontrolled caches to reduce bandwidth requirements and energy consumption. However, current GPU cache hierarchies are ine�...
Yingying Tian, Sooraj Puthoor, Joseph L. Greathous...
Read-copy update (RCU) is a shared memory synchronization mechanism with scalable synchronization-free reads that nevertheless execute correctly with concurrent updates. To guaran...
This paper describes Surge, a collection-oriented programming model that enables programmers to compose parallel computations using nested high-level data collections and operator...
Saurav Muralidharan, Michael Garland, Bryan C. Cat...
As modern hardware keeps evolving, an increasingly effective approach to develop energy efficient and high-performance solvers is to design them to work on many small size indepe...
Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stani...
This paper studies the effects of source-code optimizations on the performance, power draw, and energy consumption of a modern compute GPU. We evaluate 128 versions of two n-body ...
In this paper, we present the most extensive comparison of synchronization techniques. We evaluate 5 different synchronization techniques through a series of 31 data structure alg...
Large-scale graph-structured computation usually exhibits iterative and convergence-oriented computing nature, where input data is computed iteratively until a convergence conditi...
Chenning Xie, Rong Chen, Haibing Guan, Binyu Zang,...
Many recent multiprocessor systems are realized with a nonuniform memory architecture (NUMA) and accesses to remote memory locations take more time than local memory accesses. Opt...