Many embedded systems feature processors coupled with a small and fast scratchpad memory. To the difference with caches, allocation of data to scratchpad memory must be handled by software. The major gain is to enhance the predictability of memory accesses latencies. A compile-time dynamic allocation approach enables eviction and placement of data to the scratchpad memory at runtime.Previous dynamic scratchpad memory allocation approaches aimed to reduce average-case program execution time or the energy consumption due to memory accesses. For real-time systems, worst-case execution time is the main metric to optimize.In this paper, we propose a WCET-directed algorithm to dynamically allocate static data and stack data of a program to scratchpad memory. The granularity of placement of memory transfers (e.g. on function, basic block boundaries) is discussed from the perspective of its computation complexity and the quality of allocation.

This paper addresses the challenge of transparent data sharing within computing Grids built as cluster federations. On such platforms, the availability of storage resources may change in a dynamic way, often due to hardware failures. We focus on the problem of handling the consistency of replicated data in the presence of failures. We propose a software architecture which decouples consistency management from fault tolerance management. We illustrate this architecture with a case study showing how to design a consistency protocol using fault‐tolerant building blocks. As a proof of concept, we describe a prototype implementation of this protocol within JUXMEM, a software experimental platform for Grid data sharing, and we report on a preliminary experimental evaluation of the proposed approach. Copyright © 2006 John Wiley & Sons, Ltd.