speculative decoding and mtp optimization #1435
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Signed-off-by: Benjamin Chislett <benjamin.chislett@centml.ai>
This PR enabled a profiler for each step of the LLMEngine. The following 4 ENVs are used to control the profiler: - VLLM_ENGINE_PROFILER_ENABLED, set to true to enable device profiler. - VLLM_ENGINE_PROFILER_WARMUP_STEPS, number of steps to ignore for profiling. - VLLM_ENGINE_PROFILER_STEPS, number of steps to capture for profiling. - VLLM_ENGINE_PROFILER_REPEAT, number of cycles for (warmup + profile). > Please refer to [torch.profiler.schedule](https://pytorch.org/docs/stable/profiler.html#torch.profiler.schedule) for more details about the profiler schedule arguments. > The step in profiling means a step of the LLM engine and **exclude** the profile and warmup run in HabanaModelRunner. Please use `export VLLM_PROFILER_ENABLED=True` to enable the high-level vLLM profiler and use the result to choose the steps for detailed LLMEngine profiling.
Signed-off-by: jkyu <jiankang.yu@intel.com>
Signed-off-by: jkyu <jiankang.yu@intel.com>
Signed-off-by: jkyu <jiankang.yu@intel.com>
Signed-off-by: jkyu <jiankang.yu@intel.com>
Signed-off-by: jkyu <jiankang.yu@intel.com>
inkcherry
changed the title
reduce the communication to optimize the perf Signed-off-by: inkcherry <mingzhi.liu@intel.com> Signed-off-by: inkcherry <mingzhi.liu@intel.com>
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cc @YuJiankang @czhu15