A Replacement Technique to Maximize Task Reuse in Reconfigurable Systems

Dynamically reconfigurable hardware is a promising technology that combines in the same device both the high performance and the flexibility that many recent applications demand. However, one of its main drawbacks is the reconfiguration overhead, which involves important delays in the task execution, usually in the order of hundreds of milliseconds, as well as high energy consumption. One of the most powerful ways to tackle this problem is configuration reuse, since reusing a task does not involve any reconfiguration overhead. In this paper we propose a configuration replacement policy for reconfigurable systems that maximizes task reuse in highly dynamic environments. We have integrated this policy in an external taskgraph execution manager that applies task prefetch by loading and executing the tasks as soon as possible (ASAP). However, we have also modified this ASAP technique in order to make the replacements more flexible, by taking into account the mobility of the tasks and delaying some of the reconfigurations. In addition, this replacement policy is a hybrid design-time/run-time approach, which performs the bulk of the computations at design time in order to save run-time computations. Our results illustrate that the proposed strategy outperforms other state-ofthe-art replacement policies in terms of reuse rates and achieves near-optimal reconfiguration overhead reductions. In addition, by performing the bulk of the computations at design time, we reduce the execution time of the replacement technique by 10 times with respect to an equivalent purely run-time one

Efficient runtime placement management for high performance and reliability in COTS FPGAs

Designing high-performance, fault-tolerant multisensory electronic systems for hostile environments such as nuclear plants and outer space within the constraints of cost, power and flexibility is challenging. Issues such as ionizing radiation, extreme temperature and ageing can lead to faults in the electronics of these systems. In addition, the remote nature of these environments demands a level of flexibility and autonomy in their operations. The standard practice of using specially hardened electronic devices for such systems is not only very expensive but also has limited flexibility. This thesis proposes novel techniques that promote the use of Commercial Off-The- Shelf (COTS) reconfigurable devices to meet the challenges of high-performance systems for hostile environments. Reconfigurable hardware such as Field Programmable Gate Arrays (FPGA) have a unique combination of flexibility and high performance. The flexibility offered through features such as dynamic partial reconfiguration (DPR) can be harnessed not only to achieve cost-effective designs as a smaller area can be used to execute multiple tasks, but also to improve the reliability of a system as a circuit on one portion of the device can be physically relocated to another portion in the case of fault occurrence. However, to harness these potentials for high performance and reliability in a cost-effective manner, novel runtime management tools are required. Most runtime support tools for reconfigurable devices are based on ideal models which do not adequately consider the limitations of realistic FPGAs, in particular modern FPGAs which are increasingly heterogeneous. Specifically, these tools lack efficient mechanisms for ensuring a high utilization of FPGA resources, including the FPGA area and the configuration port and clocking resources, in a reliable manner. To ensure high utilization of reconfigurable device area, placement management is a key aspect of these tools. This thesis presents novel techniques for the management of hardware task placement on COTS reconfigurable devices for high performance and reliability. To this end, it addresses design-time issues that affect efficient hardware task placement, with a focus on reliability. It also presents techniques to maximize the utilization of the FPGA area in runtime, including techniques to minimize fragmentation. Fragmentation leads to the creation of unusable areas due to dynamic placement of tasks and the heterogeneity of the resources on the chip. Moreover, this thesis also presents an efficient task reuse mechanism to improve the availability of the internal configuration infrastructure of the FPGA for critical responsibilities like error mitigation. The task reuse scheme, unlike previous approaches, also improves the utilization of the chip area by offering defragmentation. Task relocation, which involves changing the physical location of circuits is a technique for error mitigation and high performance. Hence, this thesis also provides a functionality-based relocation mechanism for improving the number of locations to which tasks can be relocated on heterogeneous FPGAs. As tasks are relocated, clock networks need to be routed to them. As such, a reliability-aware technique of clock network routing to tasks after placement is also proposed. Finally, this thesis offers a prototype implementation and characterization of a placement management system (PMS) which is an integration of the aforementioned techniques. The performance of most of the proposed techniques are tested using data processing tasks of a NASA JPL spectrometer application. The results show that the proposed techniques have potentials to improve the reliability and performance of applications in hostile environment compared to state-of-the-art techniques. The task optimization technique presented leads to better capacity to circumvent permanent faults on COTS FPGAs compared to state-of-the-art approaches (48.6% more errors were circumvented for the JPL spectrometer application). The proposed task reuse scheme leads to approximately 29% saving in the amount of configuration time. This frees up the internal configuration interface for more error mitigation operations. In addition, the proposed PMS has a worst-case latency of less than 50% of that of state-of- the-art runtime placement systems, while maintaining the same level of placement quality and resource overhead