Energy efficiency and computing flexibility are some of the primary design constraints of heterogeneous computing. In this paper, we present FlashAbacus, a data-processing accelerator that self-governs heterogeneous kernel executions and data storage accesses by integrating many flash modules in lightweight multiprocessors. The proposed accelerator can simultaneously process data from different applications with diverse types of operational functions, and it allows multiple kernels to directly access flash without the assistance of a host-level file system or an I/O runtime library. We prototype FlashAbacus on a multicore-based PCIe platform that connects to FPGA-based flash controllers with a 20 nm node process. The evaluation results show that FlashAbacus can improve the bandwidth of data processing by 127%, while reducing energy consumption by 78.4%, as compared to a conventional method of heterogeneous computing. \blfootnote{This paper is accepted by and will be published at 2018 EuroSys. This document is presented to ensure timely dissemination of scholarly and technical work.
翻译:节能和计算灵活性是多种计算的一些主要设计制约因素。 本文介绍FlashAbacus, 这是一种数据处理加速器,通过将许多闪光模块整合到轻量多处理器中,使自我管理的不同内核处决和数据储存存取器。 拟议的加速器可以同时处理不同应用中具有不同类型操作功能的数据, 允许多个内核直接存取闪光, 而无需主机级文件系统或I/ O 运行时间库的协助。 我们将FlashAbacus原型放在一个多核心的 PCIe 平台上, 该平台将连接到基于FPGA的闪光控制器, 并使用 20 纳米节点程序。 评价结果显示, FlashAbacus 能够将数据处理的带宽提高127%, 与常规的混合计算方法相比, 将能源消耗减少78.4% 。 \ blototote{ 本文被接受, 并将在2018 Euros- Sys 发表。 。 该文件是为了确保及时传播学术和技术工作。