Name
Abstract | ||
|---|---|---|
Tensor methods have gained increasingly attention from various applications, including machine learning, quantum chemistry, healthcare analytics, social network analysis, data mining, and signal processing, to name a few. Sparse tensors and their algorithms become critical to further improve the performance of these methods and enhance the interpretability of their output. This work presents a sparse tensor algorithm benchmark suite (PASTA) for single- and multi-core CPUs. To the best of our knowledge, this is the first benchmark suite for sparse tensor world. PASTA targets on: (1) helping application users to evaluate different computer systems using its representative computational workloads; (2) providing insights to better utilize existed computer architecture and systems and inspiration for the future design. This benchmark suite is publicly released at
https://gitlab.com/tensorworld/pasta
, under version 0.1.0. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s42514-019-00012-w | CCF Transactions on High Performance Computing |
Keywords | DocType | Volume |
Sparse tensor, Tensor methods, Benchmarking, High performance computing, Sparsity | Journal | 1 |
Issue | ISSN | Citations |
2 | 2524-4922 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiajia Li | 1 | 317 | 34.53 |
| Yuchen Ma | 2 | 5 | 2.13 |
| Xiaolong Wu | 3 | 128 | 18.86 |
| Ang Li | 4 | 201 | 29.68 |
| Kevin J. Barker | 5 | 15 | 2.74 |