Pyxis: An Open-Source Performance Dataset of Sparse Accelerators

• URL: http://arxiv.org/abs/2110.04280v1
• Date: Fri, 8 Oct 2021 17:46:51 GMT
• Title: Pyxis: An Open-Source Performance Dataset of Sparse Accelerators
• Authors: Linghao Song, Yuze Chi, Jason Cong
• Abstract summary: PYXIS is a performance dataset for specialized accelerators on sparse data. PYXIS is open-source, and we are constantly growing PYXIS with new accelerator designs and performance statistics.
• Score: 10.18035715512647
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Specialized accelerators provide gains of performance and efficiency in specific domains of applications. Sparse data structures or/and representations exist in a wide range of applications. However, it is challenging to design accelerators for sparse applications because no analytic architecture or performance-level models are able to fully capture the spectrum of the sparse data. Accelerator researchers rely on real execution to get precise feedback for their designs. In this work, we present PYXIS, a performance dataset for specialized accelerators on sparse data. PYXIS collects accelerator designs and real execution performance statistics. Currently, there are 73.8 K instances in PYXIS. PYXIS is open-source, and we are constantly growing PYXIS with new accelerator designs and performance statistics. PYXIS can benefit researchers in the fields of accelerator, architecture, performance, algorithm, and many related topics.

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