FPGA dynamic and partial reconfiguration : a survey of architectures, methods, and applications

Dynamic and partial reconfiguration are key differentiating capabilities of field programmable gate arrays (FPGAs). While they have been studied extensively in academic literature, they find limited use in deployed systems. We review FPGA reconfiguration, looking at architectures built for the purpose, and the properties of modern commercial architectures. We then investigate design flows, and identify the key challenges in making reconfigurable FPGA systems easier to design. Finally, we look at applications where reconfiguration has found use, as well as proposing new areas where this capability places FPGAs in a unique position for adoption

ZyCAP : efficient partial reconfiguration management on the Xilinx Zynq

New hybrid FPGA platforms that couple processors with a reconfigurable fabric, such as the Xilinx Zynq, offer an alternative view of reconfigurable computing where software applications leverage hardware resources through the use of often reconfigured accelerators. For this to be feasible, reconfiguration overheads must be reduced so that the processor is not burdened with managing the process. We discuss partial reconfiguration (PR) on these architectures, and present an open source controller, ZyCAP, that overcomes the limitations of existing methods, offering more effective use of hardware resources in such architectures. ZyCAP combines high-throughput configuration with a high-level software interface that frees the processor from detailed PR management, making PR on the Zynq easy and efficient

Virtualized FPGA accelerators for efficient cloud computing

Hardware accelerators implement custom architectures to significantly speed up computations in a wide range of domains. As performance scaling in server-class CPUs slows, we propose the integration of hardware accelerators in the cloud as a way to maintain a positive performance trend. Field programmable gate arrays (FPGAs) represent the ideal way to integrate accelerators in the cloud, since they can be reprogrammed as needs change and allow multiple accelerators to share optimised communication infrastructure. We discuss a framework that integrates reconfigurable accelerators in a standard server with virtualised resource management and communication. We then present a case study that quantifies the efficiency benefits and break-even point for integrating FPGAs in the cloud

High throughput accelerator interface framework for a linear time-multiplexed FPGA overlay

Coarse-grained FPGA overlays improve design productivity through software-like programmability and fast compilation. However, the effectiveness of overlays as accelerators is dependent on suitable interface and programming integration into a typically processor-based computing system, an aspect which has often been neglected in evaluations of overlays. We explore the integration of a time-multiplexed FPGA overlay over a server-class PCI Express interface. We show how this integration can be optimised to maximise performance, and evaluate the area overhead. We also propose a user-friendly programming model for such an overlay accelerator system

JetStream : an open-source high-performance PCI express 3 streaming library for FPGA-to-host and FPGA-to-FPGA communication

Many FPGA-based accelerators are constrained by the available resources and multi-FPGA solutions can be necessary for building more capable systems. Available PCIe solutions provide only FPGA-to-Host communication. In this paper we present JetStream, an open-source1 modular PCIe 3 library, supporting not only fast FPGA-to-Host communication, but also allowing direct FPGA-to-FPGA communication which fully bypasses the memory subsystem. The direct mode saves memory bandwidth for multicast modes and permits to connect multiple FPGAs in various software defined topologies. We show the benefits of JetStream with a large FIR filter spanning four FPGA boards, achieving throughputs of up to 7.09 GB/s per link. Utilizing direct FPGA-to-FPGA transfers reduces the required memory bandwidth by up to 75%

Virtualized execution runtime for FPGA accelerators in the cloud

FPGAs offer high performance coupled with energy efficiency, making them extremely attractive computational resources within a cloud ecosystem. However, to achieve this integration and make them easy to program, we first need to enable users with varying expertise to easily develop cloud applications that leverage FPGAs. With the growing size of FPGAs, allocating them monolithically to users can be wasteful due to potentially low device utilization. Hence, we also need to be able to dynamically share FPGAs among multiple users. To address these concerns, we propose a methodology and a runtime system that together simplify the FPGA application development process by providing: 1) a clean abstraction with high-level APIs for easy application development; 2) a simple execution model that supports both hardware and software execution; and 3) a shared memory-model which is convenient to use for the programmers. Akin to an operating system on a computer, our lightweight runtime system enables the simultaneous execution of multiple applications by virtualizing computational resources, i.e., FPGA resources and on-board memory, and offers protection facilities to isolate applications from each other. In this paper, we illustrate how these features can be developed in a lightweight manner and quantitatively evaluate the performance overhead they introduce on a small set of applications running on our proof of concept prototype. Our results demonstrate that these features only introduce marginal performance overheads. More importantly, by sharing resources for simultaneous execution of multiple user applications, our platform improves FPGA utilization and delivers higher aggregate throughput compared to accessing the device in a time-shared manner