chrishkchris opened a new pull request #558: SINGA-487 Parallelize Computation and Communication using CUDA stream concurrency URL: https://github.com/apache/singa/pull/558 This PR deals with the Parallelization of Computation and Communication using CUDA stream concurrency, which can reduce the communication overhead. Together with the result of PR #555, here is a simple test to make sure the training is correct: ``` ubuntu@ip-172-31-29-119:~/singa/examples/autograd$ /home/ubuntu/mpich-3.3/build/bin/mpiexec --hostfile host_file python3 mnist_dist.py Starting Epoch 0: Training loss = 931.969849, training accuracy = 0.675197 Evaluation accuracy = 0.913137, Elapsed Time = 0.733470s Starting Epoch 1: Training loss = 280.136505, training accuracy = 0.910273 Evaluation accuracy = 0.954975, Elapsed Time = 0.642032s Starting Epoch 2: Training loss = 188.183517, training accuracy = 0.939837 Evaluation accuracy = 0.967619, Elapsed Time = 0.650523s Starting Epoch 3: Training loss = 147.724915, training accuracy = 0.952941 Evaluation accuracy = 0.971012, Elapsed Time = 0.639127s Starting Epoch 4: Training loss = 125.514275, training accuracy = 0.959402 Evaluation accuracy = 0.974404, Elapsed Time = 0.637774s Starting Epoch 5: Training loss = 113.583031, training accuracy = 0.963174 Evaluation accuracy = 0.974918, Elapsed Time = 0.638678s Starting Epoch 6: Training loss = 105.422485, training accuracy = 0.965895 Evaluation accuracy = 0.979852, Elapsed Time = 0.637032s Starting Epoch 7: Training loss = 94.718765, training accuracy = 0.968850 Evaluation accuracy = 0.976871, Elapsed Time = 0.638873s Starting Epoch 8: Training loss = 87.026405, training accuracy = 0.971421 Evaluation accuracy = 0.976768, Elapsed Time = 0.637387s Starting Epoch 9: Training loss = 79.878670, training accuracy = 0.973708 Evaluation accuracy = 0.981805, Elapsed Time = 0.639177s ```
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