This thesis investigates the use of massively parallel fine-grained processor arrays to increase computational performance. As processors move towards multi-core processing, more energy-efficient processors can be designed by increasing the number of processor cores on a single chip rather than increasing the clock frequency of a single processor. This can be done by making processor cores less complex, but increasing the number of processor cores on a chip. Using this philosophy, a processor core can be reduced in complexity, area, and speed to form a very small processor which can still perform basic arithmetic operations. Due to the small area occupation this can be multiplied and scaled to form a large scale parallel processor array to offer a significant performance. Following this design methodology, two fine-grained parallel processor arrays are designed which aim to achieve a small area occupation with each individual processor so that a larger array can be implemented over a given area. To demonstrate scalability and performance, SIMD parallel processor array is designed for implementation on an FPGA where each processor can be implemented using four 'slices' of a Xilinx FPGA. With such small area utilization, a large fine-grained processor can be implemented on these FPGAs. A 32 × 32 processor array is implemented and fast processing demonstrated using image processing tasks.An event-driven MIMD parallel processor array is also designed which occupies a small amount of area and can be scaled up to form much larger arrays. The event-driven approach allows the processor to enter an idle mode when no events are occurring local to the processor, reducing power consumption. The processor can switch to operational mode when events are detected. The processor core is designed with a multi-bit data path and ALU and contains its own instruction memory making the array a multi-core processor array. With area occupation of primary concern, the processor is relatively simple and connects with its four nearest direct neighbours. A small 8 × 8 prototype chip is implemented in a 65 nm CMOS technology process which can operate at a clock frequency of 80 MHz and offer a peak performance of 5.12 GOPS which can be scaled up to larger arrays.An application of the event-driven processor array is demonstrated using a simulation model of the processor. An event-driven algorithm is demonstrated to perform distributed control of distributed manipulator simulator by separating objects based on their physical properties.
|Date of Award||1 Aug 2015|
- The University of Manchester
|Supervisor||Piotr Dudek (Supervisor)|
- Processor Array
- Parallel Processing