Triton crashes on boot

### System Info

- Hardware: 8x NVIDIA H100 80GB HBM3
- Software:  NVIDIA-SMI 535.129.03             Driver Version: 535.129.03   CUDA Version: 12.4 
- tensorrtllm_backend commit: [d173386f4dd7b3ed5883dea43851b6bde5eda5c7](https://github.com/triton-inference-server/tensorrtllm_backend/commit/d173386f4dd7b3ed5883dea43851b6bde5eda5c7)

### Who can help?

_No response_

### Information

- [x] The official example scripts
- [ ] My own modified scripts

### Tasks

- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

Build container from [this commit](https://github.com/triton-inference-server/tensorrtllm_backend/commit/d173386f4dd7b3ed5883dea43851b6bde5eda5c7) (current HEAD), e.g. `DOCKER_BUILDKIT=1 docker build -t triton_trt_llm -f dockerfile/Dockerfile.trt_llm_backend .`

Follow these instructions from the top level README to build gpt2 model with fp16 TP4:
```
# Go to the tensorrt_llm/examples/gpt directory
cd tensorrt_llm/examples/gpt

# Download weights from HuggingFace Transformers
rm -rf gpt2 && git clone https://huggingface.co/gpt2-medium gpt2
pushd gpt2 && rm pytorch_model.bin model.safetensors && wget -q https://huggingface.co/gpt2-medium/resolve/main/pytorch_model.bin && popd

# Convert weights from HF Tranformers to TensorRT-LLM checkpoint
python3 convert_checkpoint.py --model_dir gpt2 \
        --dtype float16 \
        --tp_size 4 \
        --output_dir ./c-model/gpt2/fp16/4-gpu

# Build TensorRT engines
trtllm-build --checkpoint_dir ./c-model/gpt2/fp16/4-gpu \
        --gpt_attention_plugin float16 \
        --remove_input_padding enable \
        --paged_kv_cache enable \
        --gemm_plugin float16 \
        --output_dir engines/fp16/4-gpu
```

Populate triton config.pbtxt and start the triton container:
```
# Create the model repository that will be used by the Triton server
cd tensorrtllm_backend
mkdir triton_model_repo

# Copy the example models to the model repository
cp -r all_models/inflight_batcher_llm/* triton_model_repo/

# Copy the TRT engine to triton_model_repo/tensorrt_llm/1/
cp ../engines/fp16/4-gpu/* triton_model_repo/tensorrt_llm/1

docker run --rm -it --net host --shm-size=2g --ulimit memlock=-1 --ulimit stack=67108864 --gpus '"device=0,1,2,3"' -v $(pwd):/tensorrtllm_backend triton_trt_llm bash
```

And launch triton:
```
cd /tensorrtllm_backend
python3 scripts/launch_triton_server.py --world_size=4 --model_repo=/tensorrtllm_backend/triton_model_repo
```

### Expected behavior

A running Triton server serving the built engine.

### actual behavior

Crashes with these logs:

```
[TensorRT-LLM][INFO] Engine version 0.12.0.dev2024080600 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] Initializing MPI with thread mode 3
I0809 21:00:12.594083 832 libtensorrtllm.cc:55] "TRITONBACKEND_Initialize: tensorrtllm"
I0809 21:00:12.594120 832 libtensorrtllm.cc:62] "Triton TRITONBACKEND API version: 1.19"
I0809 21:00:12.594124 832 libtensorrtllm.cc:66] "'tensorrtllm' TRITONBACKEND API version: 1.19"
I0809 21:00:12.594128 832 libtensorrtllm.cc:86] "backend configuration:\n{\"cmdline\":{\"auto-complete-config\":\"false\",\"backend-directory\":\"/opt/tritonserver/backends\",\"min-compute-capability\":\"6.000000\",\"default-max-batch-size\":\"4\"}}"
I0809 21:00:12.595327 833 libtensorrtllm.cc:55] "TRITONBACKEND_Initialize: tensorrtllm"
I0809 21:00:12.595362 833 libtensorrtllm.cc:62] "Triton TRITONBACKEND API version: 1.19"
I0809 21:00:12.595367 833 libtensorrtllm.cc:66] "'tensorrtllm' TRITONBACKEND API version: 1.19"
I0809 21:00:12.595371 833 libtensorrtllm.cc:86] "backend configuration:\n{\"cmdline\":{\"auto-complete-config\":\"false\",\"backend-directory\":\"/opt/tritonserver/backends\",\"min-compute-capability\":\"6.000000\",\"default-max-batch-size\":\"4\"}}"
I0809 21:00:12.611549 834 libtensorrtllm.cc:55] "TRITONBACKEND_Initialize: tensorrtllm"
I0809 21:00:12.611587 834 libtensorrtllm.cc:62] "Triton TRITONBACKEND API version: 1.19"
I0809 21:00:12.611593 834 libtensorrtllm.cc:66] "'tensorrtllm' TRITONBACKEND API version: 1.19"
I0809 21:00:12.611598 834 libtensorrtllm.cc:86] "backend configuration:\n{\"cmdline\":{\"auto-complete-config\":\"false\",\"backend-directory\":\"/opt/tritonserver/backends\",\"min-compute-capability\":\"6.000000\",\"default-max-batch-size\":\"4\"}}"
[TensorRT-LLM][INFO] Using GPU device ids: 0,1,2,3
I0809 21:00:12.612990 832 libtensorrtllm.cc:114] "TRITONBACKEND_ModelInitialize: tensorrt_llm (version 1)"
[TensorRT-LLM][WARNING] max_beam_width is not specified, will use default value of 1
[TensorRT-LLM][WARNING] iter_stats_max_iterations is not specified, will use default value of 1000
[TensorRT-LLM][WARNING] request_stats_max_iterations is not specified, will use default value of 0
[TensorRT-LLM][WARNING] normalize_log_probs is not specified, will be set to true
[TensorRT-LLM][WARNING] max_tokens_in_paged_kv_cache is not specified, will use default value
[TensorRT-LLM][WARNING] kv_cache_free_gpu_mem_fraction is not specified, will use default value of 0.9 or max_tokens_in_paged_kv_cache
[TensorRT-LLM][WARNING] kv_cache_host_memory_bytes not set, defaulting to 0
[TensorRT-LLM][WARNING] kv_cache_onboard_blocks not set, defaulting to true
[TensorRT-LLM][WARNING] max_attention_window_size is not specified, will use default value (i.e. max_sequence_length)
[TensorRT-LLM][WARNING] sink_token_length is not specified, will use default value
[TensorRT-LLM][WARNING] enable_kv_cache_reuse is not specified, will be set to false
[TensorRT-LLM][WARNING] enable_chunked_context is not specified, will be set to false.
[TensorRT-LLM][WARNING] lora_cache_max_adapter_size not set, defaulting to 64
[TensorRT-LLM][WARNING] lora_cache_optimal_adapter_size not set, defaulting to 8
[TensorRT-LLM][WARNING] lora_cache_gpu_memory_fraction not set, defaulting to 0.05
[TensorRT-LLM][WARNING] lora_cache_host_memory_bytes not set, defaulting to 1GB
[TensorRT-LLM][WARNING] decoding_mode parameter is invalid or not specified(must be one of the {top_k, top_p, top_k_top_p, beam_search, medusa}).Using default: top_k_top_p if max_beam_width == 1, beam_search otherwise
[TensorRT-LLM][WARNING] gpu_weights_percent parameter is not specified, will use default value of 1.0
[TensorRT-LLM][WARNING] encoder_model_path is not specified, will be left empty
[TensorRT-LLM][INFO] Engine version 0.12.0.dev2024080600 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] Initializing MPI with thread mode 3
[TensorRT-LLM][INFO] Using GPU device ids: 0,1,2,3
I0809 21:00:12.614943 833 libtensorrtllm.cc:114] "TRITONBACKEND_ModelInitialize: tensorrt_llm (version 1)"
[TensorRT-LLM][WARNING] max_beam_width is not specified, will use default value of 1
[TensorRT-LLM][WARNING] iter_stats_max_iterations is not specified, will use default value of 1000
[TensorRT-LLM][WARNING] request_stats_max_iterations is not specified, will use default value of 0
[TensorRT-LLM][WARNING] normalize_log_probs is not specified, will be set to true
[TensorRT-LLM][WARNING] max_tokens_in_paged_kv_cache is not specified, will use default value
[TensorRT-LLM][WARNING] kv_cache_free_gpu_mem_fraction is not specified, will use default value of 0.9 or max_tokens_in_paged_kv_cache
[TensorRT-LLM][WARNING] kv_cache_host_memory_bytes not set, defaulting to 0
[TensorRT-LLM][WARNING] kv_cache_onboard_blocks not set, defaulting to true
[TensorRT-LLM][WARNING] max_attention_window_size is not specified, will use default value (i.e. max_sequence_length)
[TensorRT-LLM][WARNING] sink_token_length is not specified, will use default value
[TensorRT-LLM][WARNING] enable_kv_cache_reuse is not specified, will be set to false
[TensorRT-LLM][WARNING] enable_chunked_context is not specified, will be set to false.
[TensorRT-LLM][WARNING] lora_cache_max_adapter_size not set, defaulting to 64
[TensorRT-LLM][WARNING] lora_cache_optimal_adapter_size not set, defaulting to 8
[TensorRT-LLM][WARNING] lora_cache_gpu_memory_fraction not set, defaulting to 0.05
[TensorRT-LLM][WARNING] lora_cache_host_memory_bytes not set, defaulting to 1GB
[TensorRT-LLM][WARNING] decoding_mode parameter is invalid or not specified(must be one of the {top_k, top_p, top_k_top_p, beam_search, medusa}).Using default: top_k_top_p if max_beam_width == 1, beam_search otherwise
[TensorRT-LLM][WARNING] gpu_weights_percent parameter is not specified, will use default value of 1.0
[TensorRT-LLM][WARNING] encoder_model_path is not specified, will be left empty
[TensorRT-LLM][INFO] Engine version 0.12.0.dev2024080600 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] Initializing MPI with thread mode 3
[TensorRT-LLM][INFO] Using GPU device ids: 0,1,2,3
I0809 21:00:12.630739 834 libtensorrtllm.cc:114] "TRITONBACKEND_ModelInitialize: tensorrt_llm (version 1)"
[TensorRT-LLM][WARNING] max_beam_width is not specified, will use default value of 1
[TensorRT-LLM][WARNING] iter_stats_max_iterations is not specified, will use default value of 1000
[TensorRT-LLM][WARNING] request_stats_max_iterations is not specified, will use default value of 0
[TensorRT-LLM][WARNING] normalize_log_probs is not specified, will be set to true
[TensorRT-LLM][WARNING] max_tokens_in_paged_kv_cache is not specified, will use default value
[TensorRT-LLM][WARNING] kv_cache_free_gpu_mem_fraction is not specified, will use default value of 0.9 or max_tokens_in_paged_kv_cache
[TensorRT-LLM][WARNING] kv_cache_host_memory_bytes not set, defaulting to 0
[TensorRT-LLM][WARNING] kv_cache_onboard_blocks not set, defaulting to true
[TensorRT-LLM][WARNING] max_attention_window_size is not specified, will use default value (i.e. max_sequence_length)
[TensorRT-LLM][WARNING] sink_token_length is not specified, will use default value
[TensorRT-LLM][WARNING] enable_kv_cache_reuse is not specified, will be set to false
[TensorRT-LLM][WARNING] enable_chunked_context is not specified, will be set to false.
[TensorRT-LLM][WARNING] lora_cache_max_adapter_size not set, defaulting to 64
[TensorRT-LLM][WARNING] lora_cache_optimal_adapter_size not set, defaulting to 8
[TensorRT-LLM][WARNING] lora_cache_gpu_memory_fraction not set, defaulting to 0.05
[TensorRT-LLM][WARNING] lora_cache_host_memory_bytes not set, defaulting to 1GB
[TensorRT-LLM][WARNING] decoding_mode parameter is invalid or not specified(must be one of the {top_k, top_p, top_k_top_p, beam_search, medusa}).Using default: top_k_top_p if max_beam_width == 1, beam_search otherwise
[TensorRT-LLM][WARNING] gpu_weights_percent parameter is not specified, will use default value of 1.0
[TensorRT-LLM][WARNING] encoder_model_path is not specified, will be left empty
[TensorRT-LLM][INFO] Engine version 0.12.0.dev2024080600 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] Initializing MPI with thread mode 3
[TensorRT-LLM][INFO] Initialized MPI
[TensorRT-LLM][INFO] Initialized MPI
[TensorRT-LLM][INFO] Initialized MPI
[TensorRT-LLM][INFO] Initialized MPI
[TensorRT-LLM][INFO] Refreshed the MPI local session
[TensorRT-LLM][INFO] Refreshed the MPI local session
[TensorRT-LLM][INFO] Refreshed the MPI local session
[TensorRT-LLM][INFO] MPI size: 4, MPI local size: 4, rank: 2
[TensorRT-LLM][INFO] Refreshed the MPI local session
[TensorRT-LLM][INFO] MPI size: 4, MPI local size: 4, rank: 0
[TensorRT-LLM][INFO] MPI size: 4, MPI local size: 4, rank: 1
[TensorRT-LLM][INFO] Using user-specified devices: (0, 1, 2, 3)
[TensorRT-LLM][INFO] Rank 1 is using GPU 1
[TensorRT-LLM][INFO] MPI size: 4, MPI local size: 4, rank: 3
[TensorRT-LLM][INFO] Using user-specified devices: (0, 1, 2, 3)
[TensorRT-LLM][INFO] Rank 3 is using GPU 3
[TensorRT-LLM][INFO] Using user-specified devices: (0, 1, 2, 3)
[TensorRT-LLM][INFO] Rank 2 is using GPU 2
[TensorRT-LLM][INFO] Using user-specified devices: (0, 1, 2, 3)
[TensorRT-LLM][INFO] Rank 0 is using GPU 0
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 256
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 256
[TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
[TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 1024
[TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 1024
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
[TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
[TensorRT-LLM][INFO] TRTGptModel maxInputLen: 1023 = min(maxSequenceLen - 1, maxNumTokens) since context FMHA and usePackedInput are enabled
[TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: min(maxSequenceLen, maxNumTokens).
[TensorRT-LLM][INFO] Capacity Scheduler Policy: MAX_UTILIZATION
[TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 256
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 256
[TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
[TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 1024
[TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 1024
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
[TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 256
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 256
[TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
[TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 1024
[TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 1024
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
[TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
[TensorRT-LLM][INFO] TRTGptModel maxInputLen: 1023 = min(maxSequenceLen - 1, maxNumTokens) since context FMHA and usePackedInput are enabled
[TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: min(maxSequenceLen, maxNumTokens).
[TensorRT-LLM][INFO] TRTGptModel maxInputLen: 1023 = min(maxSequenceLen - 1, maxNumTokens) since context FMHA and usePackedInput are enabled
[TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: min(maxSequenceLen, maxNumTokens).
[TensorRT-LLM][INFO] Capacity Scheduler Policy: MAX_UTILIZATION
[TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
[TensorRT-LLM][INFO] Capacity Scheduler Policy: MAX_UTILIZATION
[TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 256
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 256
[TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
[TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 1024
[TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 1024
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
[TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
[TensorRT-LLM][INFO] TRTGptModel maxInputLen: 1023 = min(maxSequenceLen - 1, maxNumTokens) since context FMHA and usePackedInput are enabled
[TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: min(maxSequenceLen, maxNumTokens).
[TensorRT-LLM][INFO] Capacity Scheduler Policy: MAX_UTILIZATION
[TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
[TensorRT-LLM][INFO] Loaded engine size: 273 MiB
[TensorRT-LLM][INFO] Loaded engine size: 273 MiB
[TensorRT-LLM][INFO] Loaded engine size: 273 MiB
[TensorRT-LLM][INFO] Loaded engine size: 273 MiB
--------------------------------------------------------------------------
MPI_ABORT was invoked on rank 2 in communicator MPI_COMM_WORLD
with errorcode 1.

NOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.
You may or may not see output from other processes, depending on
exactly when Open MPI kills them.
--------------------------------------------------------------------------
[192-222-52-240:00828] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198
[192-222-52-240:00828] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198
[192-222-52-240:00828] PMIX ERROR: UNREACHABLE in file server/pmix_server.c at line 2198
[192-222-52-240:00828] 3 more processes have sent help message help-mpi-api.txt / mpi-abort
[192-222-52-240:00828] Set MCA parameter "orte_base_help_aggregate" to 0 to see all help / error messages
```

### additional notes

I've provided example with gpt2 since that's what your README references, but it repros with llama2 and llama3 models too.

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Triton crashes on boot #563

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Triton crashes on boot #563

Description

System Info

Who can help?

Information

Tasks

Reproduction

Expected behavior

actual behavior

additional notes

Metadata

Metadata

Assignees

Labels

Type

Projects

Milestone

Relationships

Development

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