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In our computation of memory consumptions, we include the memory space needed for the pattern vector, the trace file, and the intermediate data generated by the MapReduce paradigm.
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Identification of deviations from predicted or programed consumption profiles modeled by a Multichannel Structure are shown to be easily designed, tuned and implemented with low computation demand of memory and processing speed.
DAA efficiently realizes the sum-of-products computation by means of memory (LUT), adders and shift registers, without employing any multipliers.
In recent years, a class of tiled matrix decomposition algorithms has been proposed for out-of-memory computations and multi-core architectures including GPU-based heterogeneous systems.
A streaming memory system is designed to enable high-throughput computation and efficient use of memory resources.
Note that in this work as well as [12, 31] and several previous works reviewed in this paper, it is assumed that gateways are more powerful than the sensor nodes in terms of memory, computation, and communication capabilities.
Using efmtool (and also polco) [ 12], even after specifying 2 GB of memory, computation of EMs was not possible due to running out of memory.
Indeed, for a same computation time and amount of memory, our algorithms perform better than existing ones.
Because the algorithm needs to compute each stage at most twice, once in the forward pass to create the checkpoints and once during the backtrace, the overall number of stage computations of the memory-reduced algorithm is at most double what it would have been.
At high frequencies FEM and BEM based packages require huge amount of computation memory and time for their executions that DPSM technique can avoid.
Narrow slits of the in-vessel components are effectively modeled by using the element splitting method without significant increase of computation memory and time as well as without sacrificing the accuracy.
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