A Multi-layer Fpga Framework Supporting Autonomous Runtime Partial Reconfiguration

Partial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip resources. Operations are partitioned into Logic, Translation, and Reconfiguration layers along with a standardized set of Application Programming Interfaces (APIs). At each level, resource details are encapsulated and managed for efficiency and portability during operation. An MRRA mapping theory is developed to link the general logic function and area allocation information to the device related physical configuration level data by using mathematical data structure and physical constraints. In certain scenarios, configuration bit stream data can be read and modified directly for fast operations, relying on the use of similar logic functions and common interconnection resources for communication. A corresponding logic control flow is also developed to make the entire process autonomous. Several prototype MRRA systems are developed on a Xilinx Virtex II Pro platform. The Virtex II Pro on-chip PowerPC core and block RAM are employed to manage control operations while multiple physical interfaces establish and supplement autonomous reconfiguration capabilities. Area, speed and power optimization techniques are developed based on the developed Xilinx prototype. Evaluations and analysis of these prototype and techniques are performed on a number of benchmark and hashing algorithm case studies. The results indicate that based on a variety of test benches, up to 70% reduction in the resource utilization, up to 50% improvement in power consumption, and up to 10 times increase in run-time performance are achieved using the developed architecture and approaches compared with Xilinx baseline reconfiguration flow. Finally, a Genetic Algorithm (GA) for a FPGA fault tolerance case study is evaluated as a ultimate high-level application running on this architecture. It demonstrated that this is a hardware and software infrastructure that enables an FPGA to dynamically reconfigure itself efficiently under the control of a soft microprocessor core that is instantiated within the FPGA fabric. Such a system contributes to the observed benefits of intelligent control, fast reconfiguration, and low overhead

Zero-maintenance of electronic systems: Perspectives, challenges, and opportunities

Self-engineering systems that are capable of repairing themselves in-situ without the need for human decision (or intervention) could be used to achieve zero-maintenance. This philosophy is synonymous to the way in which the human body heals and repairs itself up to a point. This article synthesises issues related to an emerging area of self-healing technologies that links software and hardware mitigations strategies. Efforts are concentrated on built-in detection, masking and active mitigation that comprises self-recovery or self-repair capability, and has a focus on system resilience and recovering from fault events. Design techniques are critically reviewed to clarify the role of fault coverage, resource allocation and fault awareness, set in the context of existing and emerging printable/nanoscale manufacturing processes. The qualitative analysis presents new opportunities to form a view on the research required for a successful integration of zero-maintenance. Finally, the potential cost benefits and future trends are enumerated

New Techniques for On-line Testing and Fault Mitigation in GPUs

L'abstract è presente nell'allegato / the abstract is in the attachmen