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Merge branch 'trmt/internode_multi_qp' of github.com:deepseek-ai/DeepEP into trmt/internode_multi_qp

In the Internode Normal Kernel, when using nvshmem ibrc for RDMA data transmission, a single QP is used for data transfer between two GPUs, which limits kernel performance in network card dual-port and RoCE network scenarios.

In our optimized Internode Normal Kernel, we implemented multiple QPs for data transmission between two GPUs, setting a different QP for each channel. Additionally, we modified the transmission method from IBRC to IBGAD.

Through these optimizations, the Internode Normal Kernel achieves optimal performance in both H800 and H20 environments, with RDMA transmission performance nearly reaching the physical network performance limit. Using the current default statistical method, in 4-node H800 and H20 environments, RDMA performance can reach 60GB/s+.

Fix typo in nvshmem.patch

Fix test combine args

Fix typo in nvshmem.patch

Signed-off-by: Hao Lin <linhaomails@gmail.com>

fix: not output result in some linux system

Super tiny fix shape typo

Adjust kNumThreads of notify_dispatch

For the SMs which calculate metadata in notify_dispatch, each warp in the SM is used to calculate the metadata of one channel. The default configuration is 8 warps for 10 channels, which needs two rounds of loop. Maybe the number of warps can be configured to the number of the channels so that one loop is enough.

Super tiny fix typo

Support zero-copy for low-latency combine

Low latency kernels use rdma atomic to support AR

Allow passing output tensor in low_latency_combine

Update NVSHMEM to v3.2.5.