SIMD parallelism offers a high performance and efficient execution approach for today's broad range of portable multimedia consumer products. However, new methods are needed to meet the complex demands of high performance, embedded systems. This research explores new storage management techniques for this focused but critical application. These techniques include memory design exploration based on the application retargeting technique, storage-based systolic instruction broadcast, and systolic virtual memory to improve both the performance and efficiency of embedded SIMD systems. For an efficient storage usage by memory design space exploration in embedded SIMD systems, an analysis method for assessing storage needs and costs of a given application automatically retargeted across a spectrum of storage configuration designs was developed. Using this technique, a SIMD processing element achieves optimal area and energy efficiency with a register file containing between 8 and 12 words for given workload. This configuration is between 15% and 25% more area and energy efficient than other memory configurations being considered. Systolic instruction broadcast is a high performance and area efficient instruction broadcasting scheme with short-wire interconnects by eliminating of wire latency bottleneck found in global instruction broadcast. Three implementation methods are defined and evaluated - software method, 2-write port register file method, and bypass method. In our evaluations, due to the system's short clock cycle time and scheduler, a speedup in system performance of up to 7.5 can be achieved by the year 2010. In addition, speedup of area efficiency also can be achieved up to 7.2 for a given workload. The ability of minimizing off-chip memory access latency while maximizing access frequency by scheduling techniques along with data prefetch techniques in systolic virtual memory mechanism was evaluated using our SIMD-systolic architecture simulator. Results show that, systolic virtual off-chip memory with shared address space can achieve over 50% higher area efficiency than that of an on-chip only system for a matrix multiplication application.