Plenty of regressions in trt-llm v0.20.0
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Description
System Info
We have a range of configurations that used to build in trt 0.18.1 and does no longer build or run with the C++ Executor on trt 0.20.0rc0.
The only thing that has changed here is a dependency upgrade from trt 0.18.1 vs 0.20.0rc0
Example:
LLama-3B goes out of memory on a 16GB ram machine
s to 466 nodes requiring 905976832 bytes.
[04/29/2025-16:34:56] [TRT] [I] Total Activation Memory: 905976832 bytes
[04/29/2025-16:34:56] [TRT] [I] Total Weights Memory: 7280613888 bytes
[04/29/2025-16:34:56] [TRT] [I] Compiler backend is used during engine execution.
[04/29/2025-16:34:56] [TRT] [I] Engine generation completed in 62.5946 seconds.
[04/29/2025-16:34:56] [TRT] [I] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 1503 MiB, GPU 9949 MiB
/bin/bash: line 47: 29 Killed python3 -m builder.main --config /app/config.yaml
User GPU build job failed with status: FAILED
Llama-3-1B gets build on a L4 (16GB RAM, 24GB VRam)
only tokenizers, configuration and file/data utilities can be used.
[Coldboost] model_cache: Fetch took 1.09 seconds, of which 0.00 seconds were spent blocking.
[Coldboost] Using hot_reload: /usr/local/briton/bin/libhot_reload.so
[Coldboost] Waiting for Briton server for briton to start
[Coldboost] Waiting for Briton server for briton to start
Model terminated unexpectedly. This model does not have enough resources to run. Try upgrading to a larger instance type. Exit code: 137, reason: OOMKilled, restart count: 4
Model terminated unexpectedly. This model does not have enough resources to run. Try upgrading to a larger instance type. Exit code: 137, reason: OOMKilled, restart count: 5
Model terminated unexpectedly. This model does not have enough resources to run. Try upgrading to a larger instance type. Exit code: 137, reason: OOMKilled, restart count: 5
Llama-70B-H100:
Model terminated unexpectedly. This model does not have enough resources to run. Try upgrading to a larger instance type. Exit code: 137, reason: OOMKilled, restart count: 1
Who can help?
No response
Information
- The official example scripts
- My own modified scripts
Tasks
- An officially supported task in the
examplesfolder (such as GLUE/SQuAD, ...) - My own task or dataset (give details below)
Reproduction
Building (pretty similar to the above) and running with C++ Executor API.
Important to not that only dependencies have changed. I am sure this could be reporduced with the nvidia internal / trtion-like runtime. This is running on Baseten.co
Expected behavior
no regressions over trt 18.1
actual behavior
additional notes
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the reported builds and runs with TensorRT-LLM 0.18.1 and 0.20.0rc0 through the C++ Executor API, using the listed Llama configurations and memory logs. Compare dependency and resource behavior across versions; done means the regressions are isolated and corrected or clearly documented with a reproducible failure.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- backend, machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100