Microprocessor fault-tolerance via on-the-fly partial reconfiguration

This paper presents a novel approach to exploit FPGA dynamic partial reconfiguration to improve the fault tolerance of complex microprocessor-based systems, with no need to statically reserve area to host redundant components. The proposed method not only improves the survivability of the system by allowing the online replacement of defective key parts of the processor, but also provides performance graceful degradation by executing in software the tasks that were executed in hardware before a fault and the subsequent reconfiguration happened. The advantage of the proposed approach is that thanks to a hardware hypervisor, the CPU is totally unaware of the reconfiguration happening in real-time, and there's no dependency on the CPU to perform it. As proof of concept a design using this idea has been developed, using the LEON3 open-source processor, synthesized on a Virtex 4 FPG

An Intermediate Language and Estimator for Automated Design Space Exploration on FPGAs

We present the TyTra-IR, a new intermediate language intended as a compilation target for high-level language compilers and a front-end for HDL code generators. We develop the requirements of this new language based on the design-space of FPGAs that it should be able to express and the estimation-space in which each configuration from the design-space should be mappable in an automated design flow. We use a simple kernel to illustrate multiple configurations using the semantics of TyTra-IR. The key novelty of this work is the cost model for resource-costs and throughput for different configurations of interest for a particular kernel. Through the realistic example of a Successive Over-Relaxation kernel implemented both in TyTra-IR and HDL, we demonstrate both the expressiveness of the IR and the accuracy of our cost model.Comment: Pre-print and extended version of poster paper accepted at international symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART2015) Boston, MA, USA, June 1-2, 201

Reconfigurable framework for high-bandwidth stream-oriented data processing

Designing a digital system that implements an assortment of specialized high performance algorithms can be costly. Considerable non-recurring engineering costs are required to develop an application specific integrated circuit (ASIC). Additionally, updating or adding features to a design requires the ASIC to be redesigned and refabricated. An alternative to using an ASIC is the field programmable gate array (FPGA). The modern FPGA\u27s ability to be partially reconfigured at runtime allows for the device to have the flexibility normally associated with a processor, while also being able to implement digital logic like in an ASIC. This capability allows for multiple digital functions to be loaded into the device at runtime only as needed. This thesis focuses on developing a reconfigurable framework that enables stream-oriented applications to make more effective use of FPGA resources and to manage partial reconfiguration operations across multiple tasks. This multichannel framework addresses several shortcomings of past research that evaluated various dynamic partial reconfiguration techniques using a color space conversion (CSC) engine. This framework allows for multiple different computations to be performed simultaneously, further improving throughput and flexibility of applications implemented within it. Performance of the system is evaluated by comparing its computational throughput to previous efforts using the CSC engine as well as the performance gained from the flexible scheduling that the framework allows. Implementations using the CSC engine show that performance can be improved up to 5 times faster than previous works, as a result of exploiting parallelism

Design of an Adaptable Run-Time Reconfigurable Software-Defined Radio Processing Architecture

Processing power is a key technical challenge holding back the development of a high-performance software defined radio (SDR). Traditionally, SDR has utilized digital signal processors (DSPs), but increasingly complex algorithms, higher data rates, and multi-tasking needs have exceed the processing capabilities of modern DSPs. Reconfigurable computers, such as field-programmable gate arrays (FPGAs), are popular alternatives because of their performance gains over software for streaming data applications like SDR. However, FPGAs have not yet realized the ideal SDR because architectures have not fully utilized their partial reconfiguration (PR) capabilities to bring needed flexibility. A reconfigurable processor architecture is proposed that utilizes PR in reconfigurable computers to achieve a more sophisticated SDR. The proposed processor contains run-time swappable blocks whose parameters and interconnects are programmable. The architecture is analyzed for performance and flexibility and compared with available alternate technologies. For a sample QPSK algorithm, hardware performance gains of at least 44x are seen over modern desktop processors and DSPs while most of their flexibility and extensibility is maintained

LEAP Scratchpads: Automatic Memory and Cache Management for Reconfigurable Logic [Extended Version]

CORRECTION: The authors for entry [4] in the references should have been "E. S. Chung, J. C. Hoe, and K. Mai".Developers accelerating applications on FPGAs or other reconfigurable logic have nothing but raw memory devices in their standard toolkits. Each project typically includes tedious development of single-use memory management. Software developers expect a programming environment to include automatic memory management. Virtual memory provides the illusion of very large arrays and processor caches reduce access latency without explicit programmer instructions. LEAP scratchpads for reconfigurable logic dynamically allocate and manage multiple, independent, memory arrays in a large backing store. Scratchpad accesses are cached automatically in multiple levels, ranging from shared on-board, RAM-based, set-associative caches to private caches stored in FPGA RAM blocks. In the LEAP framework, scratchpads share the same interface as on-die RAM blocks and are plug-in replacements. Additional libraries support heap management within a storage set. Like software developers, accelerator authors using scratchpads may focus more on core algorithms and less on memory management. Two uses of FPGA scratchpads are analyzed: buffer management in an H.264 decoder and memory management within a processor microarchitecture timing model

The Potential for a GPU-Like Overlay Architecture for FPGAs

We propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely, highly parallel and pipelinable computation. In particular, our soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of 64 stages via hardware support for up to 256 concurrent thread contexts. The key new contributions of our architecture are mechanisms for managing threads and register files that maximize data-level and instruction-level parallelism while overcoming the challenges of port limitations of FPGA block memories as well as memory and pipeline latency. Through simulation of a system that (i) is programmable via NVIDIA's high-level Cg language, (ii) supports AMD's CTM r5xx GPU ISA, and (iii) is realizable on an XtremeData XD1000 FPGA-based accelerator system, we demonstrate the potential for such a system to achieve 100% utilization of a deeply pipelined floating-point datapath