Near-optimal and scalable intrasignal in-place optimization for non-overlapping and irregular access schemes

Abstract

Storage-size management techniques aim to reduce the resources required to store elements and to concurrently provide efficient addressing during element accessing. Existing techniques are less appropriate for large iteration spaces with increased numbers of irregularly spread holes. They either have to approximate the accessed regions, leading to overestimation of the final resources, or they require prohibited exploration time to find the storage size. In this work, we present a near-optimal and scalable methodology for storage-size, intrasignal, in-place optimization, that is, to compute the minimum amount of resources required to store the elements of a group (array), for irregular complex access schemes in the target domain of non-overlapping store and load accesses.

A scalable and near-optimal representation of access schemes for memory management

“…In multiple dimensions, the representation is applied per dimension, but the maximum number of concurrent alive elements derives by propagation of the sizes from the outer dimension to the inner dimensions. The propagation between dimensions depends on the intrasignal in-place case that is valid, which is decided based on the type of the final pattern entries in the representation sequence [Kritikakou et al 2013a[Kritikakou et al , 2013b. As this work focuses on the pattern-based representation, we describe the pattern entries and the operations and illustrate them in the intrasignal in-place step for the one-dimension case, as the representation is applied per dimension.…”