By Manish Verma, Peter Marwedel
This publication proposes novel reminiscence hierarchies and software program optimization thoughts for the optimum usage of reminiscence hierarchies. It offers a variety of optimizations, gradually expanding within the complexity of research and of reminiscence hierarchies. the ultimate bankruptcy covers optimization strategies for functions along with a number of techniques present in most recent embedded devices.
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Extra info for Advanced Memory Optimization Techniques for Low Power Embedded Processors
A similar albeit smaller reduction in the execution times of the benchmarks is also observed. The average reduction in the execution times due to the SA approach varies between 39% for the multisort and 18% for the dsp benchmark. A reduction of 25% and 24% in the average execution time is observed for the SA and Frac. SA approaches, respectively. 2 Multi-Processor ARM In the current subsection, the ILP based non-overlayed scratchpad allocation (SA) approach is evaluated for a multi-process edge detection benchmark.
However, for the sake of brevity, we refrain from presenting the allocation due to Frac. SA approach. 3 Related Work Non-overlayed scratchpad allocation approaches [5, 6, 14, 29, 97, 115, 134] have been thoroughly researched by numerous research groups in the past decade. The proposed approaches allocated either data variables or instruction segments or both onto one or many scratchpads. Panda et al.  were the first ones to demonstrate the effectiveness of the scratchpad memory in minimizing the energy consumption of the system.
Despite the fact that the knapsack problem is an NPcomplete problem, the solver required less than a second to compute the optimal solution for each of the benchmarks. Next, we present the greedy algorithm based fractional scratchpad allocation approach. 3 presents the greedy algorithm to solve the fractional scratchpad allocation problem. First, the algorithm sorts the memory objects according to their valence V (moi ) = E(moi , M M )/size(moi ) to compute a sorted list of memory objects SortedM O.