PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite

TL;DR

PASTA is the first comprehensive benchmark suite for evaluating sparse tensor algorithms on CPUs, aiding system comparison, optimization, and future architecture design in diverse application domains.

Contribution

This work introduces PASTA, the first benchmark suite dedicated to sparse tensor algorithms, facilitating performance evaluation and system optimization.

Findings

Enables systematic evaluation of sparse tensor computations.

Provides insights for optimizing existing computer architectures.

Supports future design of hardware tailored for sparse tensor workloads.

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 https://gitlab.com/tensorworld/pasta.