面向交互式数据中心应用的混合计算
Hybrid Computing for Interactive Datacenter Applications
AI总结：
针对FPGA启动成本高导致难以处理延迟敏感和突发工作负载的问题，提出混合FPGA-CPU计算框架及轻量级调度器Spork，利用FPGA处理稳定负载、CPU处理突发负载，实现比同构平台更高的能效和更低的成本。
摘要：
对于各种数据中心应用，现场可编程门阵列（FPGAs）比CPUs更具能效且更具成本效益。然而，对于延迟敏感和突发的工作负载，由于高昂的FPGA启动成本，这种优势难以被利用。我们提出了一种混合FPGA和CPU的计算框架，能够以合理的成本为这类工作负载利用FPGAs的能效优势。我们的核心洞察是将FPGAs用于稳定状态的工作负载，将CPUs用于短期的工作负载突发。基于这一洞察，我们设计了Spork，一个轻量级的混合调度器，能够在实践中实现这些能效和成本优势。根据期望的目标，Spork可以在能效和降低成本之间进行权衡，反之亦然。它通过FPGAs和CPUs在功耗、性能、成本和启动延迟方面的关键差异进行参数化。我们改变这一参数空间，并在生产环境和合成trace上分析各种应用和worker配置。我们对云工作负载的评估表明，能效优化的Spork不仅更具能效，而且比同构平台更便宜——对于具有严格截止时间的短应用请求，它比仅使用FPGAs能效高1.53倍且成本低2.14倍。相对于现有成本优化混合调度器的理想化版本，能效优化的Spork在成本相当的情况下提供1.2-2.4倍的更高能效，而成本优化的Spork在成本降低1.06-1.2倍的情况下提供1.1-2倍的更高能效。
英文摘要：
Field-Programmable Gate Arrays (FPGAs) are more energy efficient and cost effective than CPUs for a wide variety of datacenter applications. Yet, for latency-sensitive and bursty workloads, this advantage can be difficult to harness due to high FPGA spin-up costs. We propose that a hybrid FPGA and CPU computing framework can harness the energy efficiency benefits of FPGAs for such workloads at reasonable cost. Our key insight is to use FPGAs for stable-state workload and CPUs for short-term workload bursts. Using this insight, we design Spork, a lightweight hybrid scheduler that can realize these energy efficiency and cost benefits in practice. Depending on the desired objective, Spork can trade off energy efficiency for cost reduction and vice versa. It is parameterized with key differences between FPGAs and CPUs in terms of power draw, performance, cost, and spin-up latency. We vary this parameter space and analyze various application and worker configurations on production and synthetic traces. Our evaluation of cloud workloads shows that energy-optimized Spork is not only more energy efficient but it is also cheaper than homogeneous platforms--for short application requests with tight deadlines, it is 1.53x more energy efficient and 2.14x cheaper than using only FPGAs. Relative to an idealized version of an existing cost-optimized hybrid scheduler, energy-optimized Spork provides 1.2-2.4x higher energy efficiency at comparable cost, while cost-optimized Spork provides 1.1-2x higher energy efficiency at 1.06-1.2x lower cost.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
