Configurable data center switch architectures

In this thesis, we explore alternative architectures for implementing con_gurable Data Center Switches along with the advantages that can be provided by such switches. Our first contribution centers around determining switch architectures that can be implemented on Field Programmable Gate Array (FPGA) to provide configurable switching protocols. In the process, we identify a gap in the availability of frameworks to realistically evaluate the performance of switch architectures in data centers and contribute a simulation framework that relies on realistic data center traffic patterns. Our framework is then used to evaluate the performance of currently existing as well as newly proposed FPGA-amenable switch designs. Through collaborative work with Meng and Papaphilippou, we establish that only small-medium range switches can be implemented on today's FPGAs. Our second contribution is a novel switch architecture that integrates a custom in-network hardware accelerator with a generic switch to accelerate Deep Neural Network training applications in data centers. Our proposed accelerator architecture is prototyped on an FPGA, and a scalability study is conducted to demonstrate the trade-offs of an FPGA implementation when compared to an ASIC implementation. In addition to the hardware prototype, we contribute a light weight load-balancing and congestion control protocol that leverages the unique communication patterns of ML data-parallel jobs to enable fair sharing of network resources across different jobs. Our large-scale simulations demonstrate the ability of our novel switch architecture and light weight congestion control protocol to both accelerate the training time of machine learning jobs by up to 1.34x and benefit other latency-sensitive applications by reducing their 99%-tile completion time by up to 4.5x. As for our final contribution, we identify the main requirements of in-network applications and propose a Network-on-Chip (NoC)-based architecture for supporting a heterogeneous set of applications. Observing the lack of tools to support such research, we provide a tool that can be used to evaluate NoC-based switch architectures.Open Acces

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Impact of NoFPGA IP router architecture on link bandwidth

In today\u27s world of advanced technology numerous applications are computationally intensive. This created an opportunity for the development of new System-on-Chip (SoC) design techniques to allow easy IP cores (Intellectual Property cores) re-use and integration under time-to-market pressure. A wide range of these newly emerging design platforms is now drifting towards highly integrated System-on-Chip designs with many on-chip processing resources like processors, DSPs, and memories. Using this technique, designers can build System-on-Chip (SoC) by integrating dozens of IP cores. As the number of IP cores integrated on a chip increases, the on-chip communication and physical interconnections become a bottleneck. New System-on-Chip (SoC) design techniques are necessary to address the communication requirements for future SoC. New communication architecture, the NoFPGA (Network-on-FPGA), for future SoFPGA (System-on-FPGA) has been presented. The paper details the architecture of a NoFPGA router. The interconnecting issues in SoFGPA design methodology built in a single FPGA device are addressed. Mainly, the performance analysis of the IPRouter of both Torus and Mesh topologies is addressed. © 2008 IEEE