As the further development of single-core architectures faces seemingly insurmountable physical and technological limitations, computer designers have turned their attention to alternative approaches. One such promising alternative is the use of several smaller cores working in unison as a programmable hardware accelerator. It is clear that the vast – and, as yet, largely untapped – potential of hardware accelerators is coming to the forefront of computer architecture. There are many challenges that must be addressed for the programmable hardware accelerator to be realized in practice. In this thesis, load-balancing, on-chip communication, and an execution model are studied. Imbalanced distribution of workloads across the processing elements constitutes wasteful use of resources, which results in degrading the performance of the system. In this thesis, a hardware-based load-balancing technique is proposed, which is demonstrated to be more scalable than state-of-the-art loadbalancing techniques. To facilitate efficient communication among ever increasing number of cores, a scalable communication network is imperative. Packet switching networks-on-chip (NoC) is considered as a viable candidate for scalable communication fabric. The size of flit, which is a unit of flow control in NoC, is one of important design parameters that determine latency, throughput and cost of NoC routers. How to determine an optimal flit size is studied in this thesis and a novel router architecture is proposed, which overcomes a problem related with the flit size. This thesis also includes a new execution model and its supporting architecture. An event-driven model that is an extension of hardware description language is employed as an execution model. The dynamic scheduling and module-level prefetching for supporting the event-driven execution model are evaluated.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50319 |
| Date | 13 January 2014 |
| Creators | Lee, Junghee |
| Contributors | Kim, Jongman |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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