On the potential of tolerant region reuse for multimedia applications

The recent years have shown an interesting evolution in the mid-end to low-end embedded domain. Portable systems are growing in importance as they improve in storage capacity and in interaction capabilities with general purpose systems. Furthermore, media processing is changing the view embedded processors are designed, keeping in mind the emergence of new application domains such as those for PDA systems or for the third generation of mobile digital phones (UMTS). The performance requirements of these new kind of devices are not those of the general-purpose domain, where traditionally the premium goal is the highest performance. Embedded systems must face ever increasing real time requirements as well as power consumption constraints. Under this special scenario, instruction/region reuse arises as a promising way of increasing the performance of media embedded processors and, at the same time, reducing the power consumption. Furthermore, media and signal processing applications are a suitable target for instruction/region reuse, given the large amount of redundancy found in media data working sets. In this paper we propose a novel region reuse mechanism that takes advantage of the tolerance of media algorithms to losses in the precision of computation. By identifying regions of code where an input data set is processed into an output data set, we can reuse computational instances using the result of previous ones with a similar input data set (hence the term tolerant reuse). We will show that conventional region reuse is barely able to provide more than a 8% in reduction of executed instructions (even with significantly big tables) in a typical JPEG encoder application. On the other hand, when applying the concept of tolerance, we are able to provide a reduction of more than 25% of the number of executed instructions with tables smaller than 1KB (with only small degradations in the quality of the output image), and up to a 40% of reduction (and no visually perceptible differences) with bigger tables .

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