This work presents an automated flow for producing fault-tolerant Field Programmable Gate Array (FPGA) systems. The flow uses the TLegUp High Level Synthesis (HLS) tool to generate triplicated register-transfer level designs for algorithms expressed in the C language and Vivado design suite for their implementation on Xilinx 7-series FPGAs. TLegUp has been extended to partition the design into a number of Triple Modular Redundant (TMR) components, which can be optionally floorplanned during their implementation. Partitioning the TMR design into a network of smaller TMR components and isolating their modules through flooplanning increases system reliability. We implemented a fine- and a coarse grain approach to partition the design, whereby the former approach uses a network flow algorithm to partition the application's Data Flow Graph (DFG) at the instruction level, while the latter uses the same algorithm to partition the design at the C function level. Results reveal that both approaches provide similar reliability enhancement to the system, but function-level partitioned designs are smaller and faster.

Coarse-grained reconfigurable architectures (CGRAs) have drawn increasing attention due to their performance and flexibility advantages. Typically, CGRAs incorporate many processing elements in the form of an array, which is suitable for implementing spatial redundancy, as used in the design of fault-tolerant systems. This article introduces a recovery time model for transient faults in CGRAs. The proposed fault-tolerant CGRAs are based on triple modular redundancy and coding techniques for error detection and correction. To evaluate the model, several kernels from space computing are mapped onto the suggested architecture. We demonstrate the tradeoff between recovery time, performance, and area. In addition, the average execution time of an application including recovery time is evaluated using area-based error-rate estimates in harsh radiation environments. The results show that task partitioning is important for bounding the recovery time of applications that have long execution times. It is also shown that error-correcting code (ECC) is of limited practical value for tasks with long execution times in high radiation environments, or when the degree of task partitioning is high.

Space processing applications deployed on SRAM-based Field Programmable Gate Arrays (FPGAs) are vulnerable to radiation-induced Single Event Upsets (SEUs). Compared with the well-known SEU mitigation solution—Triple Modular Redundancy (TMR) with configuration memory scrubbing—TMR with module-based error recovery (MER) is notably more energy efficient and responsive in repairing soft-errors in the system. Unfortunately, TMR-MER systems also need to resort to scrubbing when errors occur between sub-components, such as in interconnection nets, which are not recovered by MER. This article addresses this problem by proposing a fine-grained module-based error recovery technique, which can localize and correct errors that classic MER fails to do without additional system hardware. We evaluate our proposal via fault-injection campaigns on three types of circuits implemented in Xilinx 7-Series devices. With respect to scrubbing, we observed reductions in the mean time to repair configuration memory errors of between 48.5% and 89.4%, while reductions in energy used recovering from configuration memory errors were estimated at between 77.4% and 96.1%. These improvements result in higher reliability for systems employing TMR with fine-grained reconfiguration than equivalent systems relying on scrubbing for configuration error recovery.

We present TLegUp, an extension of LegUp, that automatically generates Triple Modular Redundant designs for FPGAs from C programs. TLegUp is expected to improve the productivity of application designers for space, to allow designers to experiment with alternative application partitioning, voter insertion and fault-tolerant aware scheduling and binding algorithms, and to support the automatic insertion of the infrastructure needed to run a fault-tolerant system. In this paper, we examine TLegUp's capacity to make use of both combinational and sequential voters by triplicating a design before scheduling and binding occur. In contrast, traditional RTL-based tools are constrained to use only combinational voters so as to preserve the scheduling and binding of the design, critical path lengths are consequently increased. We compare the use of sequential and combinational voters for a range of benchmarks implemented on a Xilinx Virtex-6 FPGA in terms of: (i) maximum operating frequency, (ii) latency, (iii) execution time, and (iv) soft-error sensitivity. Compared to the use of combinational voters, the use of sequential voters reduces the application execution time on the CHStone benchmark suite by 4% on average.

Coarse-grained reconfigurable architectures have drawn increasing attention due to their merits in performance and flexibility. Typically, they have many processing elements in the form of an array, which is suitable for implementing spatial redundancy used for fault-tolerant systems design. This paper presents a purely software-level approach to implementing transient-fault-tolerance on an existing processing element array without any modification to the architecture. It includes automated design flow to construct a fault-tolerant system and mathematical modeling for analyzing system reliability. Experiments with real-world applications show the effectiveness of the proposed approaches in terms of yield enhancement and system reliability.

Coarse-grained reconfigurable architectures (CGRAs) have drawn increasing attention due to their performance and flexibility. However, their applications have been restricted to domains based on integer arithmetic since typical CGRAs support only integer arithmetic or logical operations. This paper introduces approaches to mapping applications onto CGRAs supporting both integer and floating-point arithmetic. After presenting an optimal formulation using integer linear programming, we present a fast heuristic mapping algorithm. Our experiments on randomly generated examples generate optimal mapping results using our heuristic algorithm for 97% of the examples within a few seconds. We observe similar results for practical examples from multimedia and 3-D graphics benchmarks. The applications mapped on a CGRA show up to 120 times performance improvement compared to software implementations, demonstrating the potential for application acceleration on CGRAs supporting floating-point operations.

Time-to-market pressure and the ever-growing design complexity of multiprocessor system-on-chips have demanded an efficient design environment that enables fast exploration of large design space. In this article, we introduce a new design environment, called SoCDAL, for accelerating multiprocessor system-on-chip design through fast design-space exploration targeting real-time multimedia systems. SoCDAL is a set of mostly automated tools covering system specification, hardware/software estimation, application-to-architecture mapping, simulation model generation, and system verification through simulation. For system specification, the process network model has been widely used for system specification because of its modeling capability. However, it is hard to use for real-time systems design, since its behavior cannot be estimated statically. We introduce a new approach which enables analyzing a process network model statically with some restrictions. For the hardware/software estimation, we analyze codes statically. Application-to-architecture mapping process implements a novel algorithm to support an arbitrary number of processors, with performance evaluation by static scheduling considering communication behavior. Mapping results are used to generate simulation models automatically at several transaction levels to be pipelined to a commercial tool. We show the effectiveness of our approaches by some experimental results with multimedia applications such as JPEG, H.263, and H.264 encoders, as well as an H.264 decoder.

On-chip communication design includes designing software (SW) parts (operating system, device drivers, interrupt service routines, etc.) as well as hardware (HW) parts (on-chip communication network, communication interfaces of processor/IP/memory, on-chip memory, etc.). For an efficient exploration of its design space, we need fast scheduling and timing analysis. In this work, we tackle two problems (one for SW and the other for HW) in on-chip communication design. One is to incorporate the dynamic behavior of SW (interrupt processing and context switching) into on-chip communication scheduling. The other is to reduce on-chip data storage required for on-chip communication, by sharing physical communication buffers with different communication transactions. To solve the problems, we present both ILP (integer linear programming) formulation and heuristic algorithm, which enable the designer to perform efficient onchip communication scheduling and obtain accurate timing information. Experimental results show the effectiveness of our work.