Performance-Optimum Superscalar Architecture for Embedded Applications

TL;DR

This paper investigates the optimal sizes of cache, register file, and superscalar parameters in embedded processors to maximize performance while considering area and power constraints, finding performance saturation points.

Contribution

It provides a systematic analysis of how cache, register file, and superscalar sizes affect embedded processor performance, identifying optimal parameter thresholds.

Findings

Performance saturates beyond certain cache and register file sizes.

Increasing cache size beyond the threshold decreases performance.

Optimal parameter sizes balance performance gains with area and power costs.

Abstract

Embedded applications are widely used in portable devices such as wireless phones, personal digital assistants, laptops, etc. High throughput and real time requirements are especially important in such data-intensive tasks. Therefore, architectures that provide the required performance are the most desirable. On the other hand, processor performance is severely related to the average memory access delay, number of processor registers and also size of the instruction window and superscalar parameters. Therefore, cache, register file and superscalar parameters are the major architectural concerns in designing a superscalar architecture for embedded processors. Although increasing cache and register file size leads to performance improvements in high performance embedded processors, the increased area, power consumption and memory delay are the overheads of these techniques. This paper explores the effect of cache, register file and superscalar parameters on the processor performance to specify the optimum size of these parameters for embedded applications. Experimental results show that although having bigger size of these parameters is one of the performance improvement approaches in embedded processors, however, by increasing the size of some parameters over a threshold value, performance improvement is saturated and especially in cache size, increments over this threshold value decrease the performance.