Resource recycling: putting idle resources to work on a composable accelerator

Abstract

Mobile computing platforms in the form of smart phones, netbooks, and personal digital assistants have become an integral part of our everyday lives. Moving ahead to the future, mobile multimedia support will become a key differentiating factor for customers. Features such as high-definition audio and video, video conferencing, 3D graphics, and image projection will lead to the adoption of one phone over another. However, in contrast to wireless signal processing which is dominated by vectorizable computation, mobile multimedia applications often contain complex control flow and variable computational requirements. Moreover, data access is more complex where media applications typically operate on multi-dimensional vectors of data rather than single-dimensional vectors with simple strides. To handle these complexities, composable accelerators such as the Polymorphic Pipeline Array, or PPA, present an appealing hardware platform by adding a degree of hardware configurability over existing accelerators. Hardware resources can be both statically as well as dynamically partitioned among executing tasks to maximize execution efficiency. However, an effective compilation framework is essential to partition and assign resources to make intelligent use of the available hardware. In this paper, a compilation framework is introduced that maximizes application throughput with hybrid resource partitioning of a PPA system. Static partitioning handles part of the resource assignment, but this is followed up by dynamic partitioning to identify idle resources and put them to use -- resource recycling. Experimental results show that real-time media applications can take advantage of the static and dynamic configurability of the PPA for increase. throughput.