* Down the gcc toolset version from 13 to 11
Signed-off-by: ZhanruiSunCh <184402041+ZhanruiSunCh@users.noreply.github.com>
* Update rocky8 images
Signed-off-by: ZhanruiSunCh <184402041+ZhanruiSunCh@users.noreply.github.com>
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Signed-off-by: ZhanruiSunCh <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Hao Lu <14827759+hlu1@users.noreply.github.com@users.noreply.github.com>
Co-authored-by: Hao Lu <14827759+hlu1@users.noreply.github.com@users.noreply.github.com>
* chore: Remove GptSession/V1 from TRT workflow
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove stateful decoders
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove GptSession buffers
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove GptSession utils
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove GptSession kernels
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove V1 GPT models from tests
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove gptSessionBenchmark from scripts and docs
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove gptSession IO classes
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove GptSession from test lists
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove GptSession from docs
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove useless encoder test
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove mActualBatchSize from DecoderState
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove static batching from ExecutorTest
- Updated `validateContextLogits` and `validateGenerationLogits` functions to remove the `batchingType` parameter.
- Adjusted related test functions to reflect the changes in parameter lists.
- Cleaned up the instantiation of test cases to eliminate unnecessary batchingType references.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* Add test case for kv memory estimation
* Dump running log into file and parse kv cache memory size from file
* Set bigger peak memory size for mixed percision case and test_ptp_quickstart_advanced_eagle3 case
* Revert change to usage of fraction
* use context manager to guard temp files
Signed-off-by: Hui Gao <huig@nvidia.com>
This PR adds a customized allreduce to TensorRT-LLM. The new allreduce is used for communication on PCIe-based GPUs via low-precision quantization, which can accelerate the PCIe allreduce process.
Signed-off-by: Hui Kang <hkang@nvidia.com>
Co-authored-by: Hui Kang <hkang@nvidia.com>
Support DeepSeek-R1 W4A8 on Hopper
Co-authored-by: Barry Kang <43644113+Barry-Delaney@users.noreply.github.com>
Co-authored-by: Jiang Shao <91270701+StudyingShao@users.noreply.github.com>
Signed-off-by: Barry Kang <43644113+Barry-Delaney@users.noreply.github.com>
* Add chunking to PyT heuristic.
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
* Cast tokens and batch size to ints.
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
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Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
This issue is found for tp=ep=8 on the multi-node machine due to the inconsistent PP sizes.
* Reform the workspace allocation implementation to avoid the list-out-of-range issues.
* Disable min_latency_mode under the multi-node scenario to avoid the illegal memory access issue.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* [TRTLLM-4374] Upgrade TRT 10.10.0 GA, CUDA 12.9 GA and DLFW 25.04
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
* fix review
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
* update images
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
* Update jenkins/L0_Test.groovy
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
* update image name
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
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Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
Prefetching safetensors files so that they are stored in the system file
cache. This significantly speeds up the model weight loading for the
very first run after entering the docker container.
This is beneficial because model weight loading is done layer-by-layer,
which means reading from the safetensors chunk-by-chunk, and that cannot
utilize the internet bandwidth very well, assuming that these files are
stored in some network drives. Instead, loading the whole files in bulk
can achieve higher internet bandwidth utilization.
When running with world_size>1, all ranks collaboratedly prefetch these
files.
In theory, we should add heuristics to decide whether to prefetch the
files or not, but that is beyond the scope of this commit.
For example, when the CPU memory is small, doing prefetching may result
in file cache thrashing, resulting in slower weight loading time.
Signed-off-by: Po-Han Huang <pohanh@nvidia.com>
fix for perf test script issue
Signed-off-by: Ruodi <200874449+ruodil@users.noreply.github.com>
Co-authored-by: Larry <197874197+LarryXFly@users.noreply.github.com>
* feat: Add heuristic for GroupRMSNorm kernel selection.
Implements a logistic regression model to dynamically select between:
- GroupRMSNormBaseKernel: Allocates warps proportional to sum of dimensions
(better SM occupancy in most cases)
- GroupRMSNormLargeBatch: Allocates warps proportional to max dimension
(better block scheduling in large batch scenarios)
Selection heuristic considers batch size, allocated warps, and scheduling
efficiency on the current GPU architecture. Models for Compute Capability
9.x and 10.x are trained base on nsys kernel runtime data.
The default kernel selection is the base kernel.
The python operator group_rms_norm will use the heuristic by default.
User can pick to use the base or large batch kernels as well.
Signed-off-by: Simeng Liu <simengl@nvidia.com>
* Address the comments.
Signed-off-by: Simeng Liu <simengl@nvidia.com>
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Signed-off-by: Simeng Liu <simengl@nvidia.com>
