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Specifically, we devise an infrastructure which optimizes memory usage of multiple versions for large models.
Previous approaches to reducing memory usage of deep convnets involve trading off between computation and memory usage.
A simpler calculation, by co-adding over 50, takes 3 s with a peak memory usage of 600 MB.
Numerical tests show that the computational time and memory usage of this renormalized integral equation approach can be quite competitive with the frequency-domain finite difference iterative solver.
This allowed for a decreased offloading of tasks to software, resulting in a memory usage of only 14 KB and execution time of 20 ms.
This paper presents a novel way to automatically generate custom dynamic memory managers optimizing both performance and memory usage of the target application.
The memory usage of sparse direct solvers can be the bottleneck to solve large sparse systems of linear equations of the form Ax="b.
On the basis of two real examples, it is shown that the preconditioner can significantly shorten the time needed to calculate the interior eigenvalues, despite the fact that the memory usage of the preconditioner and Hamiltionian is comparable.
Fig. 10 Memory usage of mode -O3 Fig. 11 Memory usage of mode -Os.
Fig. 5 Memory usage of the parallel implementations.
Memory usage of DPM approach in the edge router.
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