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 architecture or performance-level analytic 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.
翻译:专门加速器在特定应用领域提供性能和效率方面的收益。 数据结构或/ 和表示形式在广泛的应用中存在偏差。 然而,由于没有建筑或性能水平分析模型能够充分捕捉稀释数据的频谱,设计稀释应用程序的加速器具有挑战性。 加速器研究人员依靠实际执行来获得准确的反馈来进行设计。 在这项工作中,我们为稀释数据的专门加速器提供了PYXIS性能数据集。 PYXIS收集加速器设计和实际执行性能统计。 目前,PYXIS中存在73.8K例。 PYXIS是开源的,我们不断增加PYXIS,并有新的加速器设计和性能统计。 PYXIS可以让加速器、结构、性能、算法和许多相关主题领域的研究人员受益。