[https://nvbugs/5481434][feat] Reuse pytorch memory segments occupied by cudagraph pool #7457

HuiGao-NV · 2025-09-02T01:20:21Z

Previous PR of this change was closed automatically after retarget base branch.

Summary by CodeRabbit

Bug Fixes
- Reduced out-of-memory incidents during Mixture-of-Experts execution by reusing workspace memory across runs and CUDA graph capture.
Refactor
- Implemented internal buffer reuse for workspace tensors in DeepGemmFusedMoE, lowering allocation churn and improving memory stability.
- Added an internal recorder for allocated buffers to enable reuse across execution paths.
- No changes to public APIs or user-facing configuration.

Description

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HuiGao-NV · 2025-09-02T01:20:49Z

/bot run --add-multi-gpu-test --disable-fail-fast

tensorrt-cicd · 2025-09-02T01:26:23Z

PR_Github #17266 [ run ] triggered by Bot

coderabbitai · 2025-09-02T01:28:16Z

📝 Walkthrough

Walkthrough

Adds a capture-aware buffer reuse mechanism to DeepGemmFusedMoE’s workspace allocations in fused_moe_deepgemm.py. Introduces a class-level cache for CUDA tensors, helper functions to select/reuse buffers during graph capture vs runtime, and replaces direct allocations for three workspaces with the new allocator. No public API signatures changed.

Changes

Cohort / File(s)	Summary of Changes
DeepGemmFusedMoE workspace reuse `tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py`	Added class attribute `allocated_buffer_recorder` for buffer pools; imported `math`. Implemented `select_buffer_with_more_elements` and `get_empty` to reuse CUDA tensors across graph-capture/runtime. Replaced direct allocations for `workspace_0`, `workspace_1`, `workspace_sf` with cache-backed allocation using per-buffer pool keys.

Sequence Diagram(s)

sequenceDiagram
    autonumber
    actor Caller
    participant DeepGemmFusedMoE as DeepGemmFusedMoE
    participant Allocator as get_empty (allocator)
    participant GraphPool as Graph buffer pool
    participant RuntimePool as Runtime buffer pool
    participant CUDA as CUDA Tensor

    Caller->>DeepGemmFusedMoE: forward(...)
    DeepGemmFusedMoE->>Allocator: request workspace_X(shape, dtype, capture_flag)
    alt capture_flag == true
        Allocator->>GraphPool: lookup suitable buffer
        alt found suitable
            Allocator-->>DeepGemmFusedMoE: view/slice of graph buffer
        else not found
            Allocator->>RuntimePool: check reusable buffer
            alt runtime buffer usable
                Allocator->>GraphPool: move/record buffer for capture
                Allocator-->>DeepGemmFusedMoE: view/slice
            else none usable
                Allocator->>CUDA: allocate new tensor
                Allocator->>GraphPool: record buffer
                Allocator-->>DeepGemmFusedMoE: new tensor
            end
        end
    else capture_flag == false
        Allocator->>RuntimePool: lookup suitable buffer
        alt found suitable
            Allocator-->>DeepGemmFusedMoE: reused tensor
        else not found
            Allocator->>CUDA: allocate new tensor
            Allocator->>RuntimePool: record buffer
            Allocator-->>DeepGemmFusedMoE: new tensor
        end
    end
    Note over DeepGemmFusedMoE: Applied for workspace_0, workspace_1, workspace_sf

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Possibly related PRs

[https://nvbugs/5412562][feat] Allocate MoE workspace only when necessary (release/1.0 retargeted) #6955 — Implements capture-aware persistent workspace management for MoE in C++ (FusedMoeRunner), conceptually matching this Python-side buffer reuse.

Suggested reviewers

hlu1
jinyangyuan-nvidia
djns99
kaiyux

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coderabbitai

Actionable comments posted: 4

🧹 Nitpick comments (1)

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py (1)
1-1: Add NVIDIA copyright header.

This file is missing the required header per guidelines.

Add at the top:
# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.

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Reviewing files that changed from the base of the PR and between 14af1f0 and 01530c6.

📒 Files selected for processing (1)

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py (3 hunks)

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tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py

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tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py

🧠 Learnings (2)

📓 Common learnings

Learnt from: djns99
PR: NVIDIA/TensorRT-LLM#6915
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:4616-4626
Timestamp: 2025-08-19T03:35:20.866Z
Learning: In the MOE profiler TMA workspace preparation (cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu), the overlapping of TMA WS regions for NONE and FINALIZE variants is deliberate design to save memory space, as confirmed by djns99. The comment "reuse the same pointers to save space" reflects this intentional behavior.

📚 Learning: 2025-08-19T03:35:20.866Z

Learnt from: djns99
PR: NVIDIA/TensorRT-LLM#6915
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:4616-4626
Timestamp: 2025-08-19T03:35:20.866Z
Learning: In the MOE profiler TMA workspace preparation (cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu), the overlapping of TMA WS regions for NONE and FINALIZE variants is deliberate design to save memory space, as confirmed by djns99. The comment "reuse the same pointers to save space" reflects this intentional behavior.

Applied to files:

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py

🧬 Code graph analysis (1)

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py (1)

tensorrt_llm/quantization/utils/fp8_utils.py (2)

align (24-25)

ceil_div (10-21)

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🔇 Additional comments (1)

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py (1)

488-505: Workspace allocation switch to get_empty looks good (once helpers are fixed).

Shapes and dtypes are preserved; cache keys are distinct per workspace. No functional concerns after addressing the helper fixes above.

Please sanity-check that the largest required sizes across typical shapes are:

workspace_0: num_experts * m_max * max(hidden_size, intermediate_size)

workspace_1: num_experts * m_max * max(2*intermediate_size, hidden_size)

workspace_sf: num_experts * (align(ceil_div(fp8_dim, group_size), 4) // 4) * align(m_max, 4)

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py

tensorrt-cicd · 2025-09-02T04:32:24Z

PR_Github #17266 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #9 completed with status: 'FAILURE'

HuiGao-NV · 2025-09-02T04:50:03Z

/bot run --stage-list="B200_PCIe-PyTorch-2,GB200-PyTorch-1" --add-multi-gpu-test --disable-fail-fast

tensorrt-cicd · 2025-09-02T04:55:18Z

PR_Github #17299 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-02T09:06:00Z

PR_Github #17299 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #13 (Partly Tested) completed with status: 'SUCCESS'

HuiGao-NV · 2025-09-02T09:57:08Z

/bot run --only-multi-gpu-test --disable-fail-fast

tensorrt-cicd · 2025-09-02T10:02:11Z

PR_Github #17351 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-02T15:26:43Z

PR_Github #17351 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #17 (Partly Tested) completed with status: 'FAILURE'

HuiGao-NV · 2025-09-02T22:39:00Z

Every pipeline is green, however the stage shows as red. Retest it.

HuiGao-NV · 2025-09-02T22:39:08Z

/bot run --only-multi-gpu-test --disable-fail-fast

tensorrt-cicd · 2025-09-02T22:45:07Z

PR_Github #17416 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-03T02:03:24Z

PR_Github #17416 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #28 (Partly Tested) completed with status: 'FAILURE'

HuiGao-NV · 2025-09-03T02:20:28Z

/bot run --disable-multi-gpu-test

tensorrt-cicd · 2025-09-03T02:25:30Z

PR_Github #17448 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-03T02:49:58Z

PR_Github #17448 [ run ] completed with state FAILURE
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #32 (Partly Tested) completed with status: 'FAILURE'

HuiGao-NV · 2025-09-03T03:20:47Z

/bot run --disable-multi-gpu-test

tensorrt-cicd · 2025-09-03T03:26:11Z

PR_Github #17461 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-03T04:32:08Z

PR_Github #17461 [ run ] completed with state FAILURE
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #36 (Partly Tested) completed with status: 'FAILURE'

HuiGao-NV · 2025-09-03T04:34:48Z

/bot run --disable-multi-gpu-test --disable-fail-fast

tensorrt-cicd · 2025-09-03T04:40:20Z

PR_Github #17469 [ run ] triggered by Bot

tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py

tensorrt-cicd · 2025-09-03T17:05:49Z

PR_Github #17469 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #39 (Partly Tested) completed with status: 'FAILURE'

HuiGao-NV · 2025-09-03T22:45:38Z

/bot run --stage-list "B200_PCIe-PyTorch-1"

HuiGao-NV · 2025-09-04T00:17:15Z

/bot run --stage-list="B200_PCIe-PyTorch-1"

tensorrt-cicd · 2025-09-04T00:22:06Z

PR_Github #17581 [ run ] triggered by Bot

tensorrt-cicd · 2025-09-04T03:48:30Z

PR_Github #17581 [ run ] completed with state SUCCESS
/LLM/release-1.1.0rc2/L0_MergeRequest_PR pipeline #53 (Partly Tested) completed with status: 'SUCCESS'

… by cudagraph pool Signed-off-by: Hui Gao <huig@nvidia.com>

Signed-off-by: Hui Gao <huig@nvidia.com>

HuiGao-NV · 2025-09-04T04:08:02Z

/bot skip --comment "multi-gpu and single gpu tests all pass"

tensorrt-cicd · 2025-09-04T04:13:25Z

PR_Github #17612 [ ] completed with state FAILURE
Not allowed on merged PR

… by cudagraph pool (NVIDIA#7457) Signed-off-by: Hui Gao <huig@nvidia.com>

HuiGao-NV requested a review from a team as a code owner September 2, 2025 01:20

HuiGao-NV requested a review from mikeiovine September 2, 2025 01:20

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HuiGao-NV force-pushed the reuse_buffer_in_deepgemm_moe branch from 0c0dc9d to 33428f9 Compare September 2, 2025 22:38

HuiGao-NV requested review from litaotju and yuxianq September 3, 2025 02:04

yuxianq reviewed Sep 3, 2025

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tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py Outdated Show resolved Hide resolved

yuxianq approved these changes Sep 3, 2025

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HuiGao-NV added 5 commits September 4, 2025 03:54

[https://nvbugs/5481434][feat] Reuse pytorch memory segments occupied…

23661e5

… by cudagraph pool Signed-off-by: Hui Gao <huig@nvidia.com>

Format

ceb8392

Signed-off-by: Hui Gao <huig@nvidia.com>

Add new change

7519f36

Signed-off-by: Hui Gao <huig@nvidia.com>

Add missed variable

ab9b24a

Signed-off-by: Hui Gao <huig@nvidia.com>

Address comment

b398e7c

Signed-off-by: Hui Gao <huig@nvidia.com>

HuiGao-NV force-pushed the reuse_buffer_in_deepgemm_moe branch from 0cb5a4e to b398e7c Compare September 4, 2025 03:55

HuiGao-NV enabled auto-merge (squash) September 4, 2025 04:08

litaotju disabled auto-merge September 4, 2025 04:08

litaotju merged commit 80e1f9e into NVIDIA:release/1.1.0rc2 Sep 4, 2025
4 of 5 checks passed

HuiGao-NV added a commit to HuiGao-NV/TensorRT-LLM that referenced this pull request Sep 16, 2025

[https://nvbugs/5481434][feat] Reuse pytorch memory segments occupied…

84cb5a5

… by cudagraph pool (NVIDIA#7457) Signed-off-by: Hui Gao <huig@nvidia.com>

HuiGao-NV mentioned this pull request Sep 16, 2025

[https://nvbugs/5481434][feat] cherry-pick fix to reuse pytorch memory segments occupied by cudagraph #7747

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HuiGao-NV deleted the reuse_buffer_in_deepgemm_moe branch September 19, 2025 03:53

[https://nvbugs/5481434][feat] Reuse pytorch memory segments occupied by cudagraph pool #7457

[https://nvbugs/5481434][feat] Reuse pytorch memory segments occupied by cudagraph pool #7457

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