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The resolution of the different calculations of robust topology optimization pipeline using multi-GPU systems are compared to the classically used multi-CPU implementation achieving significant speedups.
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The implementation achieves both soundness and completeness.
The Multi-GPU implementation achieves up to a speedup of 334.9 over the CPU implementation.
The CTC implementation achieved 21.46% saving in power consumption for the VOPD benchmark.
Finally, we demonstrated that our parallel implementation achieves the speedup, predicted by the formal model.
The proposed processor FPGA implementation achieves high speed hashing up to 2 Gbps.
Our experimental evaluation shows that our implementation achieves better scalability on multi-core CPUs.
The reported WUR implementation achieved the power consumption of 37.5 μW and has sensitivity of −62.7 dBm.
Our implementation achieves a 3× speed-up toward a raw implementation without optimization, while keeping the accuracy in acceptable ranges.
These measurements show that our multi-GPU implementation achieves a peak performance of 97.36 GFLOPS in double precision.
That implementation achieves ({mathcal {O}}left (frac {N}{P}(log N ^{3}right)) time complexity with N parallel processors (and achieves a runtime that is not data dependent).
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