[https://nvbugs/5575920][fix] Fix cublas/cublasLt handle creation memory not sufficient error #8533
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📝 WalkthroughWalkthroughRuntime diagnostics and error handling added to CUDA/cuBLAS handle creation in opUtils.cpp with context and memory logging on failure. FP8 KV cache test configuration updated to include token limits via new max_tokens parameter in KvCacheConfig. Changes
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🧹 Nitpick comments (1)
tests/integration/defs/accuracy/test_llm_api_pytorch.py (1)
165-169: Consider extracting the magic number into a named constant.The value
100000appears in bothtest_fp8andtest_fp8_4gpus(lines 165 and 203). Define it as a module-level or class-level constant to improve maintainability and make the intent clearer.+# Maximum tokens for FP8 KV cache to reserve memory for cuBLAS/cuBLASLt handles +FP8_KV_CACHE_MAX_TOKENS = 100000 + class TestLlama3_1_8BInstruct(LlmapiAccuracyTestHarness):Then use it in both locations:
if fp8kv: pytorch_config["kv_cache_config"] = KvCacheConfig( dtype="fp8", - max_tokens= - 100000, # Limit tokens to prevent no room for cublas/cublasLt handles + max_tokens=FP8_KV_CACHE_MAX_TOKENS, )
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cpp/tensorrt_llm/common/opUtils.cpp(2 hunks)tests/integration/defs/accuracy/test_llm_api_pytorch.py(2 hunks)
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🧠 Learnings (1)
📚 Learning: 2025-08-14T21:04:50.248Z
Learnt from: thorjohnsen
PR: NVIDIA/TensorRT-LLM#6910
File: cpp/tensorrt_llm/batch_manager/kvCacheManager.cpp:0-0
Timestamp: 2025-08-14T21:04:50.248Z
Learning: In KV cache onboarding logic during prefill in cpp/tensorrt_llm/batch_manager/kvCacheManager.cpp, when calculating which blocks fall within the attention window, use getTokensPerBlock() to advance token indices rather than block->getUniqueTokens().size(), because the calculation needs to consider the post-prefill state where blocks will be filled to capacity, not their current token count.
Applied to files:
tests/integration/defs/accuracy/test_llm_api_pytorch.py
🧬 Code graph analysis (1)
tests/integration/defs/accuracy/test_llm_api_pytorch.py (1)
tensorrt_llm/llmapi/llm_args.py (1)
KvCacheConfig(1199-1333)
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🔇 Additional comments (1)
cpp/tensorrt_llm/common/opUtils.cpp (1)
248-270: Excellent diagnostic improvements for handle creation failures.The enhanced error handling with memory statistics and context information will significantly improve debuggability when cuBLAS/cuBLASLt handle creation fails. The suggestion to adjust
max_tokensorfree_gpu_memory_fractionin the error message aligns well with the mitigation applied in the Python tests.Also applies to: 287-309
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Signed-off-by: Wangshanshan <[email protected]>
…uce max tokens in kv cache config. Signed-off-by: Wangshanshan <[email protected]>
…uce memory fraction in kv cache config. Signed-off-by: Wangshanshan <[email protected]>
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