Parallel Computing (TOPC)


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ACM Transactions on Parallel Computing (TOPC), Volume 3 Issue 3, December 2016

Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations
Matthieu Dorier, Gabriel Antoniu, Franck Cappello, Marc Snir, Robert Sisneros, Orcun Yildiz, Shadi Ibrahim, Tom Peterka, Leigh Orf
Article No.: 15
DOI: 10.1145/2987371

With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. This variability significantly impacts the...

Adaptive Optimization Modeling of Preconditioned Conjugate Gradient on Multi-GPUs
Jiaquan Gao, Yu Wang, Jun Wang, Ronghua Liang
Article No.: 16
DOI: 10.1145/2990849

The preconditioned conjugate gradient (PCG) algorithm is a well-known iterative method for solving sparse linear systems in scientific computations. GPU-accelerated PCG algorithms for large-sized problems have attracted considerable attention...

Transparently Space Sharing a Multicore Among Multiple Processes
Timothy Creech, Rajeev Barua
Article No.: 17
DOI: 10.1145/3001910

As hardware becomes increasingly parallel and the availability of scalable parallel software improves, the problem of managing multiple multithreaded applications (processes) becomes important. Malleable processes, which can vary the number of...

Hypergraph Partitioning for Sparse Matrix-Matrix Multiplication
Grey Ballard, Alex Druinsky, Nicholas Knight, Oded Schwartz
Article No.: 18
DOI: 10.1145/3015144

We propose a fine-grained hypergraph model for sparse matrix-matrix multiplication (SpGEMM), a key computational kernel in scientific computing and data analysis whose performance is often communication bound. This model correctly describes both...