Miguel Miranda

Layer assignment techniques for low energy in multi-layered memory organisations

Nearly all platforms use a multi-layer memory hierarchy to bridge the enormous latency gap between the large off-chip memories and local register files. However, most of the previous work on HW or SW controlled techniques for layer assignment have been mainly focussed on performance. As a result, the intermediate layers have been assigned too large sizes, leading to energy inefficiency. In this paper, we present a technique that takes advantage of both the temporal locality and limited lifetime of the arrays of the application for minimum energy consumption under layer size constraints. A prototype tool has been developed and tested using two real-life applications of industrial relevance. Following this approach, we have been able to halve the energy consumed by the memory hierarchy for each of our drivers.

Analysis of high-level address code transformations for programmable processors

Memory intensive applications require considerable arithmetic for the computation and selection of the different memory access pointers. These memory address calculations often involve complex (non) linear arithmetic expressions which have to be calculated during program execution under tight timing constraints, this becoming a critical bottleneck in the overall system performance. This paper explores applicability and effectiveness of source-level optimisations (as opposed to instruction-level) for address computations in the context of multimedia. We propose and evaluate two processor-target independent source-level optimisation techniques, namely, global scope operation cost minimisation complemented with loop-invariant code hoisting, and nonlinear operator strength reduction. The transformations attempt to achieve minimal code execution within loops and reduced operator strengths. The effectiveness of the transformations is demonstrated with two real-life multimedia application kernels by comparing the improvements in the number of execution cycles, before and after applying the systematic source-level optimisations. Using state-of-the-art C compilers on several popular RISC platforms.

System-level data-format exploration for dynamically allocated data structures

System-level exploration of memory organizations is a key issue in successful implementation of data dominated applications based on dynamically allocated data structures involving records and access keys. This paper presents a formalized technique for exploring different memory data-format alternatives when only the system level functional behavior of the application has been defined. Our data-format exploration approach allows to substantially minimize the number of accessed bits by rearranging the format of the data records. The technique exploits parallelism in the data transfer by analyzing the dependencies between data-record accesses. As a result, significant reduction in memory size, bandwidth, and power are obtained. We have validated our techniques using several real-life asynchronous transfer mode cell processing applications, where we have obtained reductions in memory size (up to 20%), power (up to a 60%), and bandwidth.