OPTIMAL AREA AND PERFORMANCE MAPPING OF K-LUT BASED FPGAS

FPGA circuits are increasingly used in many fields: for rapid prototyping of new products (including fast ASIC implementation), for logic emulation, for producing a small number of a device, or if a device should be reconfigurable in use (reconfigurable computing). Determining if an arbitrary, given wide, function can be implemented by a programmable logic block, unfortunately, it is generally, a very difficult problem. This problem is called the Boolean matching problem. This paper introduces a new implemented algorithm able to map, both for area and performance, combinational networks using k-LUT based FPGAs.k-LUT based FPGAs, combinational circuits, performance-driven mapping.

Optimizing Dynamic Logic Realizations For Partial Reconfiguration Of Field Programmable Gate Arrays

Many digital logic applications can take advantage of the reconfiguration capability of Field Programmable Gate Arrays (FPGAs) to dynamically patch design flaws, recover from faults, or time-multiplex between functions. Partial reconfiguration is the process by which a user modifies one or more modules residing on the FPGA device independently of the others. Partial Reconfiguration reduces the granularity of reconfiguration to be a set of columns or rectangular region of the device. Decreasing the granularity of reconfiguration results in reduced configuration filesizes and, thus, reduced configuration times. When compared to one bitstream of a non-partial reconfiguration implementation, smaller modules resulting in smaller bitstream filesizes allow an FPGA to implement many more hardware configurations with greater speed under similar storage requirements. To realize the benefits of partial reconfiguration in a wider range of applications, this thesis begins with a survey of FPGA fault-handling methods, which are compared using performance-based metrics. Performance analysis of the Genetic Algorithm (GA) Offline Recovery method is investigated and candidate solutions provided by the GA are partitioned by age to improve its efficiency. Parameters of this aging technique are optimized to increase the occurrence rate of complete repairs. Continuing the discussion of partial reconfiguration, the thesis develops a case-study application that implements one partial reconfiguration module to demonstrate the functionality and benefits of time multiplexing and reveal the improved efficiencies of the latest large-capacity FPGA architectures. The number of active partial reconfiguration modules implemented on a single FPGA device is increased from one to eight to implement a dynamic video-processing architecture for Discrete Cosine Transform and Motion Estimation functions to demonstrate a 55-fold reduction in bitstream storage requirements thus improving partial reconfiguration capability

PRODUCTIVELY SCALING HARDWARE DESIGNS OVER INCREASING RESOURCES USING A SYSTEMATIC DESIGN ANALYSIS APPROACH

As processor development shifts from strict single core frequency scaling to het- erogeneous resource scaling two important considerations require evaluation. First, how to design systems with an increasing amount of heterogeneous resources, and second, how to maintain a designer’s productivity as the number of possible con- figurations grows. Therefore, it is necessary to determine what useful information can be gathered from existing designs to help predict or identify a design’s potential scalability, as well as, identifying which routine tasks can be automated to improve a designer’s productivity. Moreover, once this information is collected, how can this information be conveyed to the designer such that it can be used to increase overall productivity when implementing the design over increasing amounts of resources? This research looks at various approaches to analyze designs and attempts to distribute an application efficiently across a heterogeneous cluster of computing re- sources through the use of a Systematic Design Analysis flow and an assortment of productivity tools. These tools provide the designer with projections on the amount of resources needed to scale an existing design to a specified performance, as well as, projecting the performance based on a specified amount of resources. This is accomplished through the combination of static HDL profiling, component synthesis resource utilization, and runtime performance monitoring. For evaluation, four case studies are presented to demonstrate the proposed flow’s scalability on a small scale cluster of FPGAs. The results are highly favorable, providing orders of magnitude speedup with minimal intervention from the designer

Boolean Matching for Complex PLBs in LUT-based FPGAs with Application to Architecture Evaluation

In this paper, we developed Boolean matching techniques for complex programmable logic blocks (PLBs) in LUT-based FPGAs. A complex PLB can not only be used as a K-input LUT, but also can implement some wide functions of more than K variables. We apply previous and develop new functional decomposition methods to match wide functions to PLBs. We can determine exactly whether a given wide function can be implemented with a XC4000 CLB or other three PLB architectures (including the XC5200 CLB). We evaluate functional capabilities of the four PLB architectures on implementing wide functions in MCNC benchmarks. Experiments show that the XC4000 CLB can be used to implement up to 98% of 6-cuts and 88% of 7-cuts in MCNC benchmarks, while two of the other three PLB architectures have a smaller cost in terms of logic capability per silicon area. Our results are useful for designing future logic unit architectures in LUT based FPGAs