论文标题
FPGAS-AS-A-Service工具包（FAAST）
FPGAs-as-a-Service Toolkit (FaaST)
论文作者
论文摘要
高能量物理学的计算需求已经很密集，预计未来几年将大幅度增加。在这种情况下，异质计算，特别是服务计算，具有比传统计算模型的显着增长的潜力。尽管以前在异质计算领域的研究和包装集中在GPU作为加速器上，但FPGA也是一个非常有前途的选择。开发了一系列工作流程，以建立FPGA作为服务的性能功能。研究了多种不同的设备和一系列用于高能量物理的算法。对于一个小的密集网络，可以通过与GPU作为服务的数量级来改善吞吐量。对于大型卷积网络，发现吞吐量与GPU作为服务相当。这项工作代表了第一个开源FPGAS-AS-A-Service工具包。
Computing needs for high energy physics are already intensive and are expected to increase drastically in the coming years. In this context, heterogeneous computing, specifically as-a-service computing, has the potential for significant gains over traditional computing models. Although previous studies and packages in the field of heterogeneous computing have focused on GPUs as accelerators, FPGAs are an extremely promising option as well. A series of workflows are developed to establish the performance capabilities of FPGAs as a service. Multiple different devices and a range of algorithms for use in high energy physics are studied. For a small, dense network, the throughput can be improved by an order of magnitude with respect to GPUs as a service. For large convolutional networks, the throughput is found to be comparable to GPUs as a service. This work represents the first open-source FPGAs-as-a-service toolkit.
