Nov 17, 2017 · We develop a solution called Snowpack that uses static features in a statistical learning framework to choose the optimal block size parameter.
We develop a solution called Snowpack that uses static features in a statistical learning framework to choose the optimal block size parameter. It does this ...
Nov 23, 2017 · — Determining the optimal block size is, thus, an important problem. ▫ We propose a model, Snowpack, which predicts a block size with a mean.
Snowpack: Efficient Parameter Choice for GPU Kernels via Static ...
sc17.supercomputing.org › wkpr177
We develop a solution called Snowpack that uses static features in a statistical learning framework to choose the optimal block size parameter. It does this ...
Singh, R, Wood, P, Gupta, R, Bagchi, S, and Laguna, I. Snowpack: Efficient Parameter Choice for GPU Kernels via Static Analysis and Statistical Prediction.
Snowpack : efficient parameter choice for GPU kernels via static analysis and statistical prediction. Singh, Ranvijay;Wood, Paul;Gupta, Ravi;Bagchi, Saurabh ...
Snowpack: Efficient Parameter Choice for GPU Kernels via Static Analysis and Statistical Prediction. I Laguna, R Singh, P Wood, R Gupta, S Bagchi ...
Snowpack: efficient parameter choice for GPU kernels via static analysis and statistical prediction · Conference Paper. November 2017. ·. 17 Reads. ·. 3 ...
2016. Snowpack: Efficient Parameter Choice for GPU Kernels via Static Analysis and Statistical Prediction. R Singh, P Wood, R Gupta, S Bagchi, I Laguna. ScalA ...
GPUMixer: Performance-Driven Floating-Point Tuning for GPU ... Snowpack: efficient parameter choice for GPU kernels via static analysis and statistical prediction ...