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2. 修改测试脚本，降低显存占用。使用量从17G -> 8G.
Signed-off-by: lijian <lijian6@sugon.com>

Signed-off-by: lijian <lijian6@sugon.com>

Signed-off-by: lijian <lijian6@sugon.com>

Signed-off-by: lijian <lijian6@sugon.com>

Co-authored-by: Yifei Zhang <219273404+yifeizhang-c@users.noreply.github.com>

* Remove redundant TMA flushes

* Less barrier initialization overhead

* Simplify `elect_one_sync`

* Use `elect_one_sync` instead of lanes

* Minor fix

* Polish testing prints

* Refactor for internode kernels

* Better performance

* Suppress kineto output

* Add pressure test mode

* Add `x_pure_rand_e4m3` test

* Add more results into hash value

* Strengthen the barrier in `cached_notify`

* lint

* Change the timing method

* lint

* Explicitly destroy the C++ runtime and release resources.

* Small fix

* fix typo

* Add a flag to control whether explicit `destroy()` is required.

* Let forwarders use a dedicated SM

* Shuffle rdma idx

* Sender use TMA.

* Adjust the tuning chunk size.

* Modify NVL chunk layout.

* Update some combine config.

* Small lint

* Minor fix

* Overlap TMA store

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Co-authored-by: Chenggang Zhao <chenggangz@deepseek.com>

* Add TMA buffer allocation

* Use TMA for forwarders and NVL receivers

* Use lane 31 to operate TMA.

* Change rdma buffer layout.

* Use TMA to transfer scales also.

* Increase the NVL recv buffer size.

* Disable early stopping.

* Apply similar optimizations on receiver warps.

* Prevent warp divergence.

* Disable aggressive ptx by default.

* Revert using TMA to transfer scales.

* Format.

* Change the layout of dispatch NVL buffer.

* Move topk transformation to recv warps.

* Use TMA to transfer all data in foward warps

* Use TMA to store scales.

* Code lint

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Co-authored-by: Chenggang Zhao <chenggangz@deepseek.com>

* use cli arg for num_processes
Signed-off-by: youkaichao <youkaichao@gmail.com>

* update low-latency
Signed-off-by: youkaichao <youkaichao@gmail.com>

* update intranode
Signed-off-by: youkaichao <youkaichao@gmail.com>

* update internode
Signed-off-by: youkaichao <youkaichao@gmail.com>

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Signed-off-by: youkaichao <youkaichao@gmail.com>

* Support bias.

* Fix.

* Fix style.

* Add draft

* Add fast-debugging flags

* Fix several bugs

* Add sender timeout checks

* Fix stuck

* Fix bugs

* Fix bugs

let the sender SM use the channel_id, and the receiver SM use channel_id + num_channels

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+.

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