Add torch_d2d_read_benchmark_runner.py under examples/microbenchmarks/ providing PyTorch parity with jax_d2d_read_benchmark_runner.py: - #924
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…rks/` providing PyTorch parity with `jax_d2d_read_benchmark_runner.py`: - Implements symmetrical sender and receiver workflows: sender populates deterministic KV-cache tensors on TPU HBM, arms `KVCacheManager` for read, and coordinates via gRPC; receiver coordinates metadata, initiates `start_read`, polls transfer completion, computes bandwidth (Gbps and GB/s), and verifies tensor consistency byte-for-byte. - Adds target `:torch_d2d_read_benchmark_runner` in `examples/microbenchmarks/BUILD`. - Updates `examples/microbenchmarks/README.md` to document the PyTorch D2D read microbenchmark. PiperOrigin-RevId: 981398158
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Add
torch_d2d_read_benchmark_runner.pyunderexamples/microbenchmarks/providing PyTorch parity withjax_d2d_read_benchmark_runner.py:KVCacheManagerfor read, and coordinates via gRPC; receiver coordinates metadata, initiatesstart_read, polls transfer completion, computes bandwidth (Gbps and GB/s), and verifies tensor consistency byte-for-byte.:torch_d2d_read_benchmark_runnerinexamples/microbenchmarks/BUILD.examples/microbenchmarks/README.mdto document the PyTorch D2D read microbenchmark.