While (1) serverless computing is emerging as a popular form of cloud execution, datacenters are going through major changes: (2) storage dissaggregation in the system infrastructure level and (3) integration of domain-specific accelerators in the hardware level. Each of these three trends individually provide significant benefits; however, when combined the benefits diminish. Specifically, the paper makes the key observation that for serverless functions, the overhead of accessing dissaggregated persistent storage overshadows the gains from accelerators. Therefore, to benefit from all these trends in conjunction, we propose Domain-Specific Computational Storage for Serverless (DSCS-Serverless). This idea contributes a serverless model that leverages a programmable accelerator within computational storage to conjugate the benefits of acceleration and storage disaggregation simultaneously. Our results with eight applications shows that integrating a comparatively small accelerator within the storage (DSCS-Serverless) that fits within its power constrains (15 Watts), significantly outperforms a traditional disaggregated system that utilizes the NVIDIA RTX 2080 Ti GPU (250 Watts). Further, the work highlights that disaggregation, serverless model, and the limited power budget for computation in storage require a different design than the conventional practices of integrating microprocessors and FPGAs. This insight is in contrast with current practices of designing computational storage that are yet to address the challenges associated with the shifts in datacenters. In comparison with two such conventional designs that either use quad-core ARM A57 or a Xilinx FPGA, DSCS-Serverless provides 3.7x and 1.7x end-to-end application speedup, 4.3x and 1.9x energy reduction, and 3.2x and 2.3x higher cost efficiency, respectively.

翻译：虽然（1）无服务器计算正作为一种流行的云计算执行形式兴起，但数据中心正经历重大变革：（2）系统基础设施层面的存储解耦，以及（3）硬件层面的领域专用加速器集成。这三项趋势各自带来显著优势，然而当合并应用时优势却有所削弱。具体而言，论文的关键发现是：对于无服务器函数而言，访问解耦持久化存储的开销掩盖了加速器带来的收益。因此，为从这些趋势的协同中获益，我们提出了面向无服务器的领域专用计算存储（DSCS-Serverless）。这一理念贡献了一种无服务器模型，它利用计算存储中的可编程加速器，同时结合了加速与存储解耦的优势。我们的八项应用实验结果表明：在存储中集成一个符合其功耗约束（15瓦）的相对小型加速器（DSCS-Serverless）显著优于采用NVIDIA RTX 2080 Ti GPU（250瓦）的传统解耦系统。此外，本工作强调：解耦、无服务器模型以及存储计算中有限的功耗预算，需要一种不同于集成微处理器和FPGA传统实践的设计。这一见解与当前设计计算存储的做法形成对比——后者尚未应对数据中心变革带来的挑战。与两种采用四核ARM A57或Xilinx FPGA的传统方案相比，DSCS-Serverless分别实现了3.7倍和1.7倍的端到端应用加速、4.3倍和1.9倍的能量消耗降低，以及3.2倍和2.3倍的成本效率提升。