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import torch |
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import time |
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from multiprocessing import Pool, set_start_method |
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def run_on_single_gpu(device): |
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a = torch.randn(1000,1000).cuda(device) |
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b = torch.randn(1000,1000).cuda(device) |
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ta = a |
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tb = b |
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while True: |
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a = ta |
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b = tb |
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a = torch.sin(a) |
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b = torch.sin(b) |
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a = torch.cos(a) |
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b = torch.cos(b) |
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a = torch.tan(a) |
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b = torch.tan(b) |
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a = torch.exp(a) |
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b = torch.exp(b) |
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a = torch.log(a) |
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b = torch.log(b) |
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b = torch.matmul(a, b) |
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if __name__ == '__main__': |
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set_start_method('spawn') |
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print('start running') |
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num_gpus = torch.cuda.device_count() |
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pool = Pool(processes=num_gpus) |
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pool.map(run_on_single_gpu, range(num_gpus)) |
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pool.close() |
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pool.join() |
