The ideal memory system assumed by most programmers is one which has high capacity, yet allows any word to be accessed instantaneously. To make the hardware approximate this performance, an increasingly complex memory hierarchy, using caches and techniques like automatic prefetch, has evolved. However, as the gap between processor and memory speeds continues to widen, these programmer-visible mechanisms are becoming inadequate. Part of the recent increase in processor performance has been due to the introduction of programmer/compiler-visible SWAR (SIMD Within A Register) parallel processing on increasingly wide DATA LARs (Line Associative Registers) as a way to both improve data access speed and increase efficiency of SWAR processing. Although the base concept of DATA LARs predates this thesis, this thesis presents the first instruction set architecture specification complete enough to allow construction of a detailed prototype hardware design. This design was implemented and tested using a hardware simulator.

Modern processor architectures suffer from an ever increasing gap between processor and memory performance. The current memory-register model attempts to hide this gap by a system of cache memory. Line Associative Registers(LARs) are proposed as a new system to avoid the memory gap by pre-fetching and associative updating of both instructions and data. This thesis presents a fully LAR-based architecture, targeting a previously developed instruction set architecture. This architecture features an execution pipeline supporting SWAR operations, and a memory system supporting the associative behavior of LARs and lazy writeback to memory.

Due to the growing mismatch between processor performance and memory latency, many dynamic mechanisms which are “invisible” to the user have been proposed: for example, trace caches and automatic pre-fetch units. However, these dynamic mechanisms have become inadequate due to implicit memory accesses that have become so expensive. On the other hand, compiler-visible mechanisms like SWAR (SIMD Within A Register) and LARs (Line Associative Registers) are potentially more effective at improving data access performance. This thesis investigates applying the same ideas to improve instruction access. ILAR (Instruction LARs) store instructions in wide registers. Instruction blocks are explicitly loaded into ILAR, using block compression to enhance memory bandwidth. The control flow of the program then refers to instructions directly by their position within an ILAR, rather than by lengthy memory addresses. Because instructions are accessed directly from within registers, there is no implicit instruction fetch from memory. This thesis proposes an instruction set architecture for ILAR, investigates a mechanism to load ILAR using the best available block compression algorithm and also develop hardware descriptions for both ILAR and a conventional memory cache model so that performance comparisons could be made on the instruction fetch stage.