The increasing use of hardware processing accelerators tailored for specific applications, such as the Vision Processing Unit (VPU) for image recognition, further increases developers' configuration, development, and management overhead. Developers have successfully used fully automated elastic cloud services such as serverless computing to counter these additional efforts and shorten development cycles for applications running on CPUs. Unfortunately, current cloud solutions do not yet provide these simplifications for applications that require hardware acceleration. However, as the development of specialized hardware acceleration continues to provide performance and cost improvements, it will become increasingly important to enable ease of use in the cloud. In this paper, we present an initial design and implementation of Hardless, an extensible and generalized serverless computing architecture that can support workloads for arbitrary hardware accelerators. We show how Hardless can scale across different commodity hardware accelerators and support a variety of workloads using the same execution and programming model common in serverless computing today.
翻译:为特定应用而专门设计的硬件处理加速器的使用日益增多,例如用于图像识别的图像处理股(VPU),进一步增加了开发者的配置、开发和管理间接费用。开发者成功地使用了完全自动化的弹性云服务,如无服务器计算,以抵消这些额外努力,缩短了在CPU上运行的应用开发周期。不幸的是,目前的云溶液尚未为需要加快硬件的应用提供这些简化。然而,随着专门硬件加速器的开发继续提供性能和成本改进,使云层使用方便将变得越来越重要。在本文件中,我们介绍了无硬件、可扩展和普遍的无服务器计算结构的初步设计和实施,这种结构能够支持任意硬件加速器的工作量。我们展示了无硬件如何跨越不同商品硬件加速器的规模,支持使用当今无服务器计算中常见的相同执行和编程模式的各种工作量。