[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend #7257

bigPYJ1151 · 2024-08-07T09:01:52Z

This PR provides corresponding CPU kernels of the compressed-tensor INT8 W8A8, based on oneDNN, to enable lowering compressed-tensor operations to CPU device.

Both of the static and dynamic mode are supported, and verified with related unit tests.

We initially got ~40% (static) and ~30% (dynamic) throughput improvement on llama3-8b model, with limited accuracy drop.

Tasks	Dtype	PPL
wikitext-2	BF16	9.9479
	W8A8	10.6414

PR Checklist (Click to Expand)

Thank you for your contribution to vLLM! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM maintain the code quality and improve the efficiency of the review process.

PR Title and Classification

Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:

[Bugfix] for bug fixes.
[CI/Build] for build or continuous integration improvements.
[Doc] for documentation fixes and improvements.
[Model] for adding a new model or improving an existing model. Model name should appear in the title.
[Frontend] For changes on the vLLM frontend (e.g., OpenAI API server, LLM class, etc.)
[Kernel] for changes affecting CUDA kernels or other compute kernels.
[Core] for changes in the core vLLM logic (e.g., LLMEngine, AsyncLLMEngine, Scheduler, etc.)
[Hardware][Vendor] for hardware-specific changes. Vendor name should appear in the prefix (e.g., [Hardware][AMD]).
[Misc] for PRs that do not fit the above categories. Please use this sparingly.

Note: If the PR spans more than one category, please include all relevant prefixes.

Code Quality

The PR need to meet the following code quality standards:

We adhere to Google Python style guide and Google C++ style guide.
Pass all linter checks. Please use format.sh to format your code.
The code need to be well-documented to ensure future contributors can easily understand the code.
Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.
Please add documentation to docs/source/ if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.

Notes for Large Changes

Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with rfc-required and might not go through the PR.

What to Expect for the Reviews

The goal of the vLLM team is to be a transparent reviewing machine. We would like to make the review process transparent and efficient and make sure no contributor feel confused or frustrated. However, the vLLM team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process:

After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.
After the PR is assigned, the reviewer will provide status update every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM team.
After the review, the reviewer will put an action-required label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.
Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.

Thank You

Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM. Your contributions make vLLM a great tool for everyone!

github-actions · 2024-08-07T09:02:06Z

👋 Hi! Thank you for contributing to the vLLM project.
Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run fastcheck CI which consists a small and essential subset of CI tests to quickly catch errors. You can run other CI tests on top of default ones by unblocking the steps in your fast-check build on Buildkite UI.

Once the PR is approved and ready to go, please make sure to run full CI as it is required to merge (or just use auto-merge).

To run full CI, you can do one of these:

Comment /ready on the PR
Add ready label to the PR
Enable auto-merge.

🚀

bigPYJ1151 · 2024-08-15T10:01:28Z

/ready

bigPYJ1151 · 2024-08-15T10:33:52Z

Hi @robertgshaw2-neuralmagic @mgoin @WoosukKwon, I think this PR is ready. Would you please help to review it? Thanks!

mgoin

This looks reasonable, but could you implement a CPU test for this?

Dockerfile.cpu

csrc/cpu/quant.cpp

mgoin · 2024-08-17T17:29:37Z

csrc/cpu/torch_bindings.cpp

+  ops.def(
+      "cutlass_scaled_mm(Tensor! out, Tensor a,"
+      "                  Tensor b, Tensor a_scales,"
+      "                  Tensor b_scales, Tensor? bias) -> ()");
+  ops.impl("cutlass_scaled_mm", torch::kCPU, &int8_scaled_mm);


I think it is confusing to call this cpu implementation cutlass_scaled_mm, especially since this only supports int8 while the GPU cutlass_scaled_mm supports fp8 and int8. I would prefer to keep int8 and possibly dnnl in the name.

I understand reusing this name likely provides some ease in re-using the testing we have for cutlass_scaled_mm, so I'm open to thoughts here. cc @tlrmchlsmth

Using the same function signature makes the kernel replacement seamlessly. The kernel for CPU will check the input types and throw error message when they are not INT8.

Maybe change cutlass_scaled_mm to a general name is more clear, like scaled_mm or compressed_tensor_scaled_mm.

Okay that is fair enough to land now for easy functionality

Maybe change cutlass_scaled_mm to a general name is more clear, like scaled_mm

I'm in favor of this as long as we maintain a consistent interface. (I don't think compressed_tensor_scaled_mm is right though, since we use the kernels for other model formats, like fb_gemm)

mgoin · 2024-08-17T17:32:15Z

vllm/platforms/interface.py

    @staticmethod
-    def get_device_capability(device_id: int = 0) -> Tuple[int, int]:
-        raise NotImplementedError
+    def get_device_capability(device_id: int = 0) -> Optional[Tuple[int, int]]:
+        return None


Maybe we should implement a CPU device capability? Curious on your thoughts @youkaichao

I would prefer to provide explicit feature checking interfaces, like support_compressed_tensor_fp8, which will make the Platform more extensible and portable.

mgoin · 2024-08-17T17:35:09Z

tests/kernels/test_cutlass.py

-CUDA_DEVICES = [
-    f"cuda:{i}" for i in range(1 if torch.cuda.device_count() == 1 else 2)
-]
+from vllm.utils import is_cpu


Like the previous mention on overloading the name cutlass_scaled_mm, I think it makes sense to duplicate a separate kernel test for CPU gemm

I appreciate the kernel testing but I would like to see an e2e test making sure model loading, weight packing, etc works since this PR plugs into compressed-tensors - just loading the model and generating a few tokens should be sufficient

We can use cases from test_compressed_tensors.py and execute E2E tests to verify the feature workflow on the CPU backend.

The kernel tests will be keep internally and executed regularly.

zhouyuan · 2024-09-09T03:14:14Z

Hi @mgoin gentle ping, would you please kindly help to take a look again?

thanks, -yuan

mgoin

This looks to be in a good place, I just would like to see more care placed on the short-circuit in _check_scheme_supported. It would be great if you could start implementing a CPU platform class so we could check for hardware features like avx512

mgoin · 2024-09-10T16:46:51Z

csrc/cpu/torch_bindings.cpp

+  ops.def(
+      "cutlass_scaled_mm(Tensor! out, Tensor a,"
+      "                  Tensor b, Tensor a_scales,"
+      "                  Tensor b_scales, Tensor? bias) -> ()");
+  ops.impl("cutlass_scaled_mm", torch::kCPU, &int8_scaled_mm);


Okay that is fair enough to land now for easy functionality

mgoin · 2024-09-10T16:48:11Z

vllm/executor/cpu_executor.py

+def _verify_and_get_parallel_config(config: ParallelConfig) -> ParallelConfig:
+    config.distributed_executor_backend = "mp"
+    return config


It might be worth leaving a log here saying that we are overriding X to "mp"

mgoin · 2024-09-10T17:46:09Z

vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors.py

+                    f"Current capability: {capability}.")
+            return supported
+        else:
+            return True


If capability is None, we say the scheme is supported? This does not seem like good logic to do for all CT schemes, but I'm not sure how to get around this.. Could you at least put a warning here that we couldn't detect device capability and are allowing the scheme to pass

I noticed this function is only used to checking FP8 support, so it should return False on non-cuda devices by default.

This reverts commit 9eeddea.

This reverts commit d9bcfb2.

bigPYJ1151 · 2024-09-11T16:31:44Z

Hi @mgoin , thanks for your comments! I made some modification based on the comments. For now, the Instruction set checking is done during the compilation time. I added a basic CpuPlatform, we can try to move the checking into it at next.

mgoin

I appreciate the changes a lot, this looks good to me!

youkaichao · 2024-09-12T00:57:56Z

vllm/config.py

@@ -876,7 +876,8 @@ def __init__(
            from vllm.executor import ray_utils
            backend = "mp"
            ray_found = ray_utils.ray_is_available()
-            if cuda_device_count_stateless() < self.world_size:
+            if (torch.cuda.is_available()


weight loading tests start to fail after this pr , I think this line is to blame. cc @mgoin

…m-project#7257)

ProExpertProg · 2024-09-12T16:01:29Z

@bigPYJ1151 could you take a look at #7270 - I changed the ops bindings for quantization that you added to the CU backend in this PR

…m-project#7257)

[Bugfix] Streamed tool calls now more strictly follow OpenAI's format; ensures Vercel AI SDK compatibility (vllm-project#8272) [Frontend] Add progress reporting to run_batch.py (vllm-project#8060) Co-authored-by: Adam Lugowski <adam.lugowski@parasail.io> [Bugfix] Correct adapter usage for cohere and jamba (vllm-project#8292) [Misc] GPTQ Activation Ordering (vllm-project#8135) [Misc] Fused MoE Marlin support for GPTQ (vllm-project#8217) Add NVIDIA Meetup slides, announce AMD meetup, and add contact info (vllm-project#8319) [Bugfix] Fix missing `post_layernorm` in CLIP (vllm-project#8155) [CI/Build] enable ccache/scccache for HIP builds (vllm-project#8327) [Frontend] Clean up type annotations for mistral tokenizer (vllm-project#8314) [CI/Build] Enabling kernels tests for AMD, ignoring some of then that fail (vllm-project#8130) Fix ppc64le buildkite job (vllm-project#8309) [Spec Decode] Move ops.advance_step to flash attn advance_step (vllm-project#8224) [Misc] remove peft as dependency for prompt models (vllm-project#8162) [MISC] Keep chunked prefill enabled by default with long context when prefix caching is enabled (vllm-project#8342) [Bugfix] lookahead block table with cuda graph max capture (vllm-project#8340) [Bugfix] Ensure multistep lookahead allocation is compatible with cuda graph max capture (vllm-project#8340) [Core/Bugfix] pass VLLM_ATTENTION_BACKEND to ray workers (vllm-project#8172) [CI/Build][Kernel] Update CUTLASS to 3.5.1 tag (vllm-project#8043) [Misc] Skip loading extra bias for Qwen2-MOE GPTQ models (vllm-project#8329) [Bugfix] Fix InternVL2 vision embeddings process with pipeline parallel (vllm-project#8299) [Hardware][NV] Add support for ModelOpt static scaling checkpoints. (vllm-project#6112) [model] Support for Llava-Next-Video model (vllm-project#7559) Co-authored-by: Roger Wang <ywang@roblox.com> Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> [Frontend] Create ErrorResponse instead of raising exceptions in run_batch (vllm-project#8347) [Model][VLM] Add Qwen2-VL model support (vllm-project#7905) Co-authored-by: Roger Wang <136131678+ywang96@users.noreply.github.com> Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vllm-project#7257) [CI/Build] Excluding test_moe.py from AMD Kernels tests for investigation (vllm-project#8373) [Bugfix] Add missing attributes in mistral tokenizer (vllm-project#8364) [Kernel][Misc] register ops to prevent graph breaks (vllm-project#6917) Co-authored-by: Sage Moore <sage@neuralmagic.com> [Misc] Move device options to a single place (vllm-project#8322) [Speculative Decoding] Test refactor (vllm-project#8317) Co-authored-by: youkaichao <youkaichao@126.com> Pixtral (vllm-project#8377) Co-authored-by: Roger Wang <ywang@roblox.com> Bump version to v0.6.1 (vllm-project#8379) [MISC] Dump model runner inputs when crashing (vllm-project#8305) [misc] remove engine_use_ray (vllm-project#8126) [TPU] Use Ray for default distributed backend (vllm-project#8389) Fix the AMD weight loading tests (vllm-project#8390) [Bugfix]: Fix the logic for deciding if tool parsing is used (vllm-project#8366) [Gemma2] add bitsandbytes support for Gemma2 (vllm-project#8338) [Misc] Raise error when using encoder/decoder model with cpu backend (vllm-project#8355) [Misc] Use RoPE cache for MRoPE (vllm-project#8396) [torch.compile] hide slicing under custom op for inductor (vllm-project#8384) [Hotfix][VLM] Fixing max position embeddings for Pixtral (vllm-project#8399) [Bugfix] Fix InternVL2 inference with various num_patches (vllm-project#8375) Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [Model] Support multiple images for qwen-vl (vllm-project#8247) Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [BugFix] lazy init _copy_stream to avoid torch init wrong gpu instance (vllm-project#8403) [BugFix] Fix Duplicate Assignment in Hermes2ProToolParser (vllm-project#8423) [Bugfix] Offline mode fix (vllm-project#8376) Signed-off-by: Joe Runde <Joseph.Runde@ibm.com> [multi-step] add flashinfer backend (vllm-project#7928) [Core] Add engine option to return only deltas or final output (vllm-project#7381) [Bugfix] multi-step + flashinfer: ensure cuda graph compatible (vllm-project#8427) [Hotfix][Core][VLM] Disable chunked prefill by default and prefix caching for multimodal models (vllm-project#8425) [CI/Build] Disable multi-node test for InternVL2 (vllm-project#8428) [Hotfix][Pixtral] Fix multiple images bugs (vllm-project#8415) [Bugfix] Fix weight loading issue by rename variable. (vllm-project#8293) [Misc] Update Pixtral example (vllm-project#8431) [BugFix] fix group_topk (vllm-project#8430) [Core] Factor out input preprocessing to a separate class (vllm-project#7329) [Bugfix] Mapping physical device indices for e2e test utils (vllm-project#8290) [Bugfix] Bump fastapi and pydantic version (vllm-project#8435) [CI/Build] Update pixtral tests to use JSON (vllm-project#8436) [Bugfix] Fix async log stats (vllm-project#8417) [bugfix] torch profiler bug for single gpu with GPUExecutor (vllm-project#8354) bump version to v0.6.1.post1 (vllm-project#8440) [CI/Build] Enable InternVL2 PP test only on single node (vllm-project#8437) [doc] recommend pip instead of conda (vllm-project#8446) [Misc] Skip loading extra bias for Qwen2-VL GPTQ-Int8 (vllm-project#8442) [misc][ci] fix quant test (vllm-project#8449) [Installation] Gate FastAPI version for Python 3.8 (vllm-project#8456) [plugin][torch.compile] allow to add custom compile backend (vllm-project#8445) [CI/Build] Reorganize models tests (vllm-project#7820) [Doc] Add oneDNN installation to CPU backend documentation (vllm-project#8467) [HotFix] Fix final output truncation with stop string + streaming (vllm-project#8468) bump version to v0.6.1.post2 (vllm-project#8473) [Hardware][intel GPU] bump up ipex version to 2.3 (vllm-project#8365) Co-authored-by: Yan Ma <yan.ma@intel.com> [Kernel][Hardware][Amd]Custom paged attention kernel for rocm (vllm-project#8310) [Model] support minicpm3 (vllm-project#8297) Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [torch.compile] fix functionalization (vllm-project#8480) [torch.compile] add a flag to disable custom op (vllm-project#8488) [TPU] Implement multi-step scheduling (vllm-project#8489) [Bugfix][Model] Fix Python 3.8 compatibility in Pixtral model by updating type annotations (vllm-project#8490) [Bugfix][Kernel] Add `IQ1_M` quantization implementation to GGUF kernel (vllm-project#8357) [Kernel] Enable 8-bit weights in Fused Marlin MoE (vllm-project#8032) Co-authored-by: Dipika <dipikasikka1@gmail.com> [Frontend] Expose revision arg in OpenAI server (vllm-project#8501) [BugFix] Fix clean shutdown issues (vllm-project#8492) [Bugfix][Kernel] Fix build for sm_60 in GGUF kernel (vllm-project#8506) [Kernel] AQ AZP 3/4: Asymmetric quantization kernels (vllm-project#7270) [doc] update doc on testing and debugging (vllm-project#8514) [Bugfix] Bind api server port before starting engine (vllm-project#8491) [perf bench] set timeout to debug hanging (vllm-project#8516) [misc] small qol fixes for release process (vllm-project#8517) [Bugfix] Fix 3.12 builds on main (vllm-project#8510) Signed-off-by: Joe Runde <Joseph.Runde@ibm.com> [refactor] remove triton based sampler (vllm-project#8524) [Frontend] Improve Nullable kv Arg Parsing (vllm-project#8525) Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> [Misc][Bugfix] Disable guided decoding for mistral tokenizer (vllm-project#8521) [torch.compile] register allreduce operations as custom ops (vllm-project#8526) [Misc] Limit to ray[adag] 2.35 to avoid backward incompatible change (vllm-project#8509) Signed-off-by: Rui Qiao <ruisearch42@gmail.com> [Benchmark] Support sample from HF datasets and image input for benchmark_serving (vllm-project#8495) [Encoder decoder] Add cuda graph support during decoding for encoder-decoder models (vllm-project#7631) [Feature][kernel] tensor parallelism with bitsandbytes quantization (vllm-project#8434) [Model] Add mistral function calling format to all models loaded with "mistral" format (vllm-project#8515) Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> [Misc] Don't dump contents of kvcache tensors on errors (vllm-project#8527) [Bugfix] Fix TP > 1 for new granite (vllm-project#8544) Signed-off-by: Joe Runde <Joseph.Runde@ibm.com> [doc] improve installation doc (vllm-project#8550) Co-authored-by: Andy Dai <76841985+Imss27@users.noreply.github.com> [CI/Build] Excluding kernels/test_gguf.py from ROCm (vllm-project#8520) [Kernel] Change interface to Mamba causal_conv1d_update for continuous batching (vllm-project#8012) [CI/Build] fix Dockerfile.cpu on podman (vllm-project#8540) [Misc] Add argument to disable FastAPI docs (vllm-project#8554) [CI/Build] Avoid CUDA initialization (vllm-project#8534) [CI/Build] Update Ruff version (vllm-project#8469) Signed-off-by: Aaron Pham <contact@aarnphm.xyz> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> [Core][Bugfix][Perf] Introduce `MQLLMEngine` to avoid `asyncio` OH (vllm-project#8157) Co-authored-by: Nick Hill <nickhill@us.ibm.com> Co-authored-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Co-authored-by: Robert Shaw <114415538+robertgshaw2-neuralmagic@users.noreply.github.com> Co-authored-by: Simon Mo <simon.mo@hey.com> [Core] *Prompt* logprobs support in Multi-step (vllm-project#8199) [Core] zmq: bind only to 127.0.0.1 for local-only usage (vllm-project#8543) Signed-off-by: Russell Bryant <rbryant@redhat.com> [Model] Support Solar Model (vllm-project#8386) Co-authored-by: Michael Goin <michael@neuralmagic.com> [AMD][ROCm]Quantization methods on ROCm; Fix _scaled_mm call (vllm-project#8380) Co-authored-by: Alexei-V-Ivanov-AMD <156011006+Alexei-V-Ivanov-AMD@users.noreply.github.com> Co-authored-by: Michael Goin <michael@neuralmagic.com> [Kernel] Change interface to Mamba selective_state_update for continuous batching (vllm-project#8039) [BugFix] Nonzero exit code if MQLLMEngine startup fails (vllm-project#8572) [Bugfix] add `dead_error` property to engine client (vllm-project#8574) Signed-off-by: Joe Runde <Joseph.Runde@ibm.com> [Kernel] Remove marlin moe templating on thread_m_blocks (vllm-project#8573) Co-authored-by: lwilkinson@neuralmagic.com [Bugfix] [Encoder-Decoder] Bugfix for encoder specific metadata construction during decode of encoder-decoder models. (vllm-project#8545) Revert "[Misc][Bugfix] Disable guided decoding for mistral tokenizer" (vllm-project#8593) [Bugfix] fixing sonnet benchmark bug in benchmark_serving.py (vllm-project#8616) [MISC] remove engine_use_ray in benchmark_throughput.py (vllm-project#8615) [Frontend] Use MQLLMEngine for embeddings models too (vllm-project#8584) [Kernel][Amd] Add fp8 kv cache support for rocm custom paged attention (vllm-project#8577) [Core] simplify logits resort in _apply_top_k_top_p (vllm-project#8619) [Doc] Add documentation for GGUF quantization (vllm-project#8618) Create SECURITY.md (vllm-project#8642) [CI/Build] Re-enabling Entrypoints tests on ROCm, excluding ones that fail (vllm-project#8551) [Misc] guard against change in cuda library name (vllm-project#8609) [Bugfix] Fix Phi3.5 mini and MoE LoRA inference (vllm-project#8571) [bugfix] [AMD] add multi-step advance_step to ROCmFlashAttentionMetadata (vllm-project#8474) [Core] Support Lora lineage and base model metadata management (vllm-project#6315) [Model] Add OLMoE (vllm-project#7922) [CI/Build] Removing entrypoints/openai/test_embedding.py test from ROCm build (vllm-project#8670) [Bugfix] Validate SamplingParam n is an int (vllm-project#8548) [Misc] Show AMD GPU topology in `collect_env.py` (vllm-project#8649) [Bugfix] Config got an unexpected keyword argument 'engine' (vllm-project#8556) [Bugfix][Core] Fix tekken edge case for mistral tokenizer (vllm-project#8640) [Doc] neuron documentation update (vllm-project#8671) Signed-off-by: omrishiv <327609+omrishiv@users.noreply.github.com> [Hardware][AWS] update neuron to 2.20 (vllm-project#8676) Signed-off-by: omrishiv <327609+omrishiv@users.noreply.github.com> [Bugfix] Fix incorrect llava next feature size calculation (vllm-project#8496) [Core] Rename `PromptInputs` and `inputs`(vllm-project#8673) [MISC] add support custom_op check (vllm-project#8557) Co-authored-by: youkaichao <youkaichao@126.com> [Core] Factor out common code in `SequenceData` and `Sequence` (vllm-project#8675) [beam search] add output for manually checking the correctness (vllm-project#8684) [Kernel] Build flash-attn from source (vllm-project#8245) [VLM] Use `SequenceData.from_token_counts` to create dummy data (vllm-project#8687) [Doc] Fix typo in AMD installation guide (vllm-project#8689) [Kernel][Triton][AMD] Remove tl.atomic_add from awq_gemm_kernel, 2-5x speedup MI300, minor improvement for MI250 (vllm-project#8646) [dbrx] refactor dbrx experts to extend FusedMoe class (vllm-project#8518) [Kernel][Bugfix] Delete some more useless code in marlin_moe_ops.cu (vllm-project#8643) [Bugfix] Refactor composite weight loading logic (vllm-project#8656) [ci][build] fix vllm-flash-attn (vllm-project#8699) [Model] Refactor BLIP/BLIP-2 to support composite model loading (vllm-project#8407) [Misc] Use NamedTuple in Multi-image example (vllm-project#8705) Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> [MISC] rename CudaMemoryProfiler to DeviceMemoryProfiler (vllm-project#8703) [Model][VLM] Add LLaVA-Onevision model support (vllm-project#8486) Co-authored-by: litianjian <litianjian@bytedance.com> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> Co-authored-by: Roger Wang <ywang@roblox.com> Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [SpecDec][Misc] Cleanup, remove bonus token logic. (vllm-project#8701) [build] enable existing pytorch (for GH200, aarch64, nightly) (vllm-project#8713) [misc] upgrade mistral-common (vllm-project#8715) [Bugfix] Avoid some bogus messages RE CUTLASS's revision when building (vllm-project#8702) [Bugfix] Fix CPU CMake build (vllm-project#8723) Co-authored-by: Yuan <yuan.zhou@intel.com> [Bugfix] fix docker build for xpu (vllm-project#8652) [Core][Frontend] Support Passing Multimodal Processor Kwargs (vllm-project#8657) Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> [Hardware][CPU] Refactor CPU model runner (vllm-project#8729) [Bugfix][CPU] fix missing input intermediate_tensors in the cpu_model_runner (vllm-project#8733) [Model] Support pp for qwen2-vl (vllm-project#8696) [VLM] Fix paligemma, fuyu and persimmon with transformers 4.45 : use config.text_config.vocab_size (vllm-project#8707) [CI/Build] use setuptools-scm to set __version__ (vllm-project#4738) Co-authored-by: youkaichao <youkaichao@126.com> [Kernel] (2/N) Machete - Integrate into CompressedTensorsWNA16 and GPTQMarlin (vllm-project#7701) Co-authored-by: mgoin <michael@neuralmagic.com> Co-authored-by: Divakar Verma <137818590+divakar-amd@users.noreply.github.com> Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com> [Kernel][LoRA] Add assertion for punica sgmv kernels (vllm-project#7585) [Core] Allow IPv6 in VLLM_HOST_IP with zmq (vllm-project#8575) Signed-off-by: Russell Bryant <rbryant@redhat.com> Fix typical acceptance sampler with correct recovered token ids (vllm-project#8562) Add output streaming support to multi-step + async while ensuring RequestOutput obj reuse (vllm-project#8335) [Hardware][AMD] ROCm6.2 upgrade (vllm-project#8674) Fix tests in test_scheduler.py that fail with BlockManager V2 (vllm-project#8728) re-implement beam search on top of vllm core (vllm-project#8726) Co-authored-by: Brendan Wong <bjwpokemon@gmail.com> Revert "[Core] Rename `PromptInputs` to `PromptType`, and `inputs` to `prompt`" (vllm-project#8750) [MISC] Skip dumping inputs when unpicklable (vllm-project#8744) [Core][Model] Support loading weights by ID within models (vllm-project#7931) [Model] Expose Phi3v num_crops as a mm_processor_kwarg (vllm-project#8658) Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk> [Bugfix] Fix potentially unsafe custom allreduce synchronization (vllm-project#8558) [Kernel] Split Marlin MoE kernels into multiple files (vllm-project#8661) Co-authored-by: mgoin <michael@neuralmagic.com> [Frontend] Batch inference for llm.chat() API (vllm-project#8648) Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk> Co-authored-by: Roger Wang <ywang@roblox.com> Co-authored-by: Roger Wang <136131678+ywang96@users.noreply.github.com> [Bugfix] Fix torch dynamo fixes caused by `replace_parameters` (vllm-project#8748) [CI/Build] fix setuptools-scm usage (vllm-project#8771) [misc] soft drop beam search (vllm-project#8763) [[Misc]Upgrade bitsandbytes to the latest version 0.44.0 (vllm-project#8768) [Core][Bugfix] Support prompt_logprobs returned with speculative decoding (vllm-project#8047) Signed-off-by: Travis Johnson <tsjohnso@us.ibm.com> [Core] Adding Priority Scheduling (vllm-project#5958) [Bugfix] Use heartbeats instead of health checks (vllm-project#8583) Fix test_schedule_swapped_simple in test_scheduler.py (vllm-project#8780) [Bugfix][Kernel] Implement acquire/release polyfill for Pascal (vllm-project#8776) Fix tests in test_chunked_prefill_scheduler which fail with BlockManager V2 (vllm-project#8752) [BugFix] Propagate 'trust_remote_code' setting in internvl and minicpmv (vllm-project#8250) [Hardware][CPU] Enable mrope and support Qwen2-VL on CPU backend (vllm-project#8770) [Bugfix] load fc bias from config for eagle (vllm-project#8790) [Frontend] OpenAI server: propagate usage accounting to FastAPI middleware layer (vllm-project#8672) [Bugfix] Ray 2.9.x doesn't expose available_resources_per_node (vllm-project#8767) Signed-off-by: darthhexx <darthhexx@gmail.com> [Misc] Fix minor typo in scheduler (vllm-project#8765) [CI/Build][Bugfix][Doc][ROCm] CI fix and doc update after ROCm 6.2 upgrade (vllm-project#8777) [Kernel] Fullgraph and opcheck tests (vllm-project#8479) [[Misc]] Add extra deps for openai server image (vllm-project#8792) [VLM][Bugfix] internvl with num_scheduler_steps > 1 (vllm-project#8614) rename PromptInputs and inputs with backward compatibility (vllm-project#8760) [Frontend] MQLLMEngine supports profiling. (vllm-project#8761) [Misc] Support FP8 MoE for compressed-tensors (vllm-project#8588) Revert "rename PromptInputs and inputs with backward compatibility (vllm-project#8760) (vllm-project#8810) [Model] Add support for the multi-modal Llama 3.2 model (vllm-project#8811) Co-authored-by: simon-mo <xmo@berkeley.edu> Co-authored-by: Chang Su <chang.s.su@oracle.com> Co-authored-by: Simon Mo <simon.mo@hey.com> Co-authored-by: Roger Wang <136131678+ywang96@users.noreply.github.com> Co-authored-by: Roger Wang <ywang@roblox.com> [Doc] Update doc for Transformers 4.45 (vllm-project#8817) [Misc] Support quantization of MllamaForCausalLM (vllm-project#8822) [Misc] Update config loading for Qwen2-VL and remove Granite (vllm-project#8837) [Build/CI] Upgrade to gcc 10 in the base build Docker image (vllm-project#8814) [Docs] Add README to the build docker image (vllm-project#8825) [CI/Build] Fix missing ci dependencies (vllm-project#8834) [misc][installation] build from source without compilation (vllm-project#8818) [ci] Soft fail Entrypoints, Samplers, LoRA, Decoder-only VLM (vllm-project#8872) Signed-off-by: kevin <kevin@anyscale.com> [Bugfix] Include encoder prompts len to non-stream api usage response (vllm-project#8861) [Misc] Change dummy profiling and BOS fallback warns to log once (vllm-project#8820) [Bugfix] Fix print_warning_once's line info (vllm-project#8867) fix validation: Only set tool_choice `auto` if at least one tool is provided (vllm-project#8568) [Bugfix] Fixup advance_step.cu warning (vllm-project#8815) [BugFix] Fix test breakages from transformers 4.45 upgrade (vllm-project#8829) [Installation] Allow lower versions of FastAPI to maintain Ray 2.9 compatibility (vllm-project#8764) [Feature] Add support for Llama 3.1 and 3.2 tool use (vllm-project#8343) Signed-off-by: Max de Bayser <mbayser@br.ibm.com> [Core] rename`PromptInputs` and `inputs` (vllm-project#8876) [misc] fix collect env (vllm-project#8894) [MISC] Fix invalid escape sequence '\' (vllm-project#8830) Signed-off-by: Peter Pan <Peter.Pan@daocloud.io> [Bugfix][VLM] Fix Fuyu batching inference with `max_num_seqs>1` (vllm-project#8892) [TPU] Update pallas.py to support trillium (vllm-project#8871) [torch.compile] use empty tensor instead of None for profiling (vllm-project#8875) [Kernel] AQ AZP 4/4: Integrate asymmetric quantization to linear method (vllm-project#7271) [Bugfix] fix for deepseek w4a16 (vllm-project#8906) Co-authored-by: mgoin <michael@neuralmagic.com> [Core] Multi-Step + Single Step Prefills via Chunked Prefill code path (vllm-project#8378) Co-authored-by: Varun Sundar Rabindranath <varun@neuralmagic.com> [misc][distributed] add VLLM_SKIP_P2P_CHECK flag (vllm-project#8911) [Core] Priority-based scheduling in async engine (vllm-project#8850) [misc] fix wheel name (vllm-project#8919) [Bugfix][Intel] Fix XPU Dockerfile Build (vllm-project#7824) Signed-off-by: tylertitsworth <tyler.titsworth@intel.com> Co-authored-by: youkaichao <youkaichao@126.com> [Misc] Remove vLLM patch of `BaichuanTokenizer` (vllm-project#8921) [Bugfix] Fix code for downloading models from modelscope (vllm-project#8443) [Bugfix] Fix PP for Multi-Step (vllm-project#8887) [CI/Build] Update models tests & examples (vllm-project#8874) Co-authored-by: Roger Wang <ywang@roblox.com> [Frontend] Make beam search emulator temperature modifiable (vllm-project#8928) Co-authored-by: Eduard Balzin <nfunctor@yahoo.fr> [Bugfix] Support testing prefill throughput with benchmark_serving.py --hf-output-len 1 (vllm-project#8891) [doc] organize installation doc and expose per-commit docker (vllm-project#8931) [Core] Improve choice of Python multiprocessing method (vllm-project#8823) Signed-off-by: Russell Bryant <rbryant@redhat.com> Co-authored-by: youkaichao <youkaichao@126.com> [Bugfix] Block manager v2 with preemption and lookahead slots (vllm-project#8824) [Bugfix] Fix Marlin MoE act order when is_k_full == False (vllm-project#8741) Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com> [CI/Build] Add test decorator for minimum GPU memory (vllm-project#8925) [Build/CI] Set FETCHCONTENT_BASE_DIR to one location for better caching (vllm-project#8930) [Model] Support Qwen2.5-Math-RM-72B (vllm-project#8896) [Model][LoRA]LoRA support added for MiniCPMV2.5 (vllm-project#7199) [BugFix] Fix seeded random sampling with encoder-decoder models (vllm-project#8870) Co-authored-by: Roger Wang <ywang@roblox.com> [Misc] Fix typo in BlockSpaceManagerV1 (vllm-project#8944) [Frontend] Added support for HF's new `continue_final_message` parameter (vllm-project#8942) [Kernel][Model] Varlen prefill + Prefill chunking support for mamba kernels and Jamba model (vllm-project#8533)

…m-project#7257) Signed-off-by: Alvant <alvasian@yandex.ru>

…m-project#7257) Signed-off-by: Amit Garg <mitgarg17495@gmail.com>

bigPYJ1151 marked this pull request as draft August 7, 2024 09:01

bigPYJ1151 mentioned this pull request Aug 7, 2024

[RFC] Initial Support for CPUs #3654

Open

4 tasks

WoosukKwon added the x86 CPU label Aug 8, 2024

bigPYJ1151 force-pushed the int8 branch from 8caabc9 to b09b5c7 Compare August 15, 2024 09:31

github-actions bot added the ready ONLY add when PR is ready to merge/full CI is needed label Aug 15, 2024

bigPYJ1151 marked this pull request as ready for review August 15, 2024 10:01

mgoin reviewed Aug 16, 2024

View reviewed changes

Dockerfile.cpu Show resolved Hide resolved

csrc/cpu/quant.cpp Show resolved Hide resolved

bigPYJ1151 force-pushed the int8 branch from b52f4bc to 9eeddea Compare August 17, 2024 15:57

mgoin reviewed Aug 17, 2024

View reviewed changes

bigPYJ1151 force-pushed the int8 branch from ab3b29c to 98aabd2 Compare August 26, 2024 05:22

bigPYJ1151 force-pushed the int8 branch from f094e97 to 8f87781 Compare September 3, 2024 08:09

robertgshaw2-neuralmagic mentioned this pull request Sep 3, 2024

Using Quantized Models with vLLM CPU Backend vllm-project/llm-compressor#134

Closed

bigPYJ1151 force-pushed the int8 branch 2 times, most recently from 646e1d9 to 12a859f Compare September 6, 2024 05:00

mgoin reviewed Sep 10, 2024

View reviewed changes

bigPYJ1151 added 11 commits September 11, 2024 06:04

support W8A8

c059f33

add oneDNN

a9e7f00

fix

fe9b55b

format

f02e0d9

trigger

68af6c2

format

b9a2bba

enable kernel tests

25875c6

retrigger

1ec8d94

Revert "enable kernel tests"

1874c2e

This reverts commit 9eeddea.

enable model test

b96c9df

format

11e8379

bigPYJ1151 added 6 commits September 11, 2024 06:07

fix core binding.

7441b3f

fix cmake

1c40481

Revert "fix cmake"

89fc49d

This reverts commit d9bcfb2.

fix compile

e802d0a

fix ray dep

269f7e7

Add cpuplatform

c42c8d8

bigPYJ1151 force-pushed the int8 branch from ae1b51a to c42c8d8 Compare September 11, 2024 07:47

set fp8 check as false by default.

fa3bbde

mgoin approved these changes Sep 11, 2024

View reviewed changes

WoosukKwon merged commit 0b952af into vllm-project:main Sep 11, 2024
69 of 71 checks passed

youkaichao reviewed Sep 12, 2024

View reviewed changes

dtrifiro pushed a commit to opendatahub-io/vllm that referenced this pull request Sep 12, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

e05ea88

…m-project#7257)

NickLucche mentioned this pull request Sep 12, 2024

gha: use vllm v0.6.1 for testing opendatahub-io/vllm-tgis-adapter#125

Merged

zhouyuan mentioned this pull request Sep 18, 2024

[Feature]: Quantisation Support with CPU Backend #8547

Open

1 task

Jeffwan pushed a commit to aibrix/vllm that referenced this pull request Sep 19, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

3b14880

…m-project#7257)

MengqingCao pushed a commit to MengqingCao/vllm that referenced this pull request Sep 30, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

774c4c6

…m-project#7257)

siddharth9820 pushed a commit to axonn-ai/vllm that referenced this pull request Sep 30, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

fbabe29

…m-project#7257)

Alvant pushed a commit to compressa-ai/vllm that referenced this pull request Oct 26, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

508e3d7

…m-project#7257) Signed-off-by: Alvant <alvasian@yandex.ru>

garg-amit pushed a commit to garg-amit/vllm that referenced this pull request Oct 28, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend (vll…

ebb9640

…m-project#7257) Signed-off-by: Amit Garg <mitgarg17495@gmail.com>

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend #7257

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend #7257

bigPYJ1151 commented Aug 7, 2024 •

edited

Loading

github-actions bot commented Aug 7, 2024

bigPYJ1151 commented Aug 15, 2024

bigPYJ1151 commented Aug 15, 2024

mgoin left a comment

mgoin Aug 17, 2024

bigPYJ1151 Aug 18, 2024 •

edited

Loading

mgoin Sep 10, 2024

tlrmchlsmth Sep 10, 2024

mgoin Aug 17, 2024

bigPYJ1151 Aug 18, 2024

mgoin Aug 17, 2024

bigPYJ1151 Aug 18, 2024

zhouyuan commented Sep 9, 2024 •

edited

Loading

mgoin left a comment

mgoin Sep 10, 2024

mgoin Sep 10, 2024

mgoin Sep 10, 2024

bigPYJ1151 Sep 11, 2024

bigPYJ1151 commented Sep 11, 2024

mgoin left a comment

youkaichao Sep 12, 2024

ProExpertProg commented Sep 12, 2024

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend #7257

[Hardware][Intel] Support compressed-tensor W8A8 for CPU backend #7257

Conversation

bigPYJ1151 commented Aug 7, 2024 • edited Loading

PR Title and Classification

Code Quality

Notes for Large Changes

What to Expect for the Reviews

Thank You

github-actions bot commented Aug 7, 2024

bigPYJ1151 commented Aug 15, 2024

bigPYJ1151 commented Aug 15, 2024

mgoin left a comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

bigPYJ1151 Aug 18, 2024 • edited Loading

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

zhouyuan commented Sep 9, 2024 • edited Loading

mgoin left a comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

bigPYJ1151 commented Sep 11, 2024

mgoin left a comment

Choose a reason for hiding this comment

Choose a reason for hiding this comment

ProExpertProg commented Sep 12, 2024

bigPYJ1151 commented Aug 7, 2024 •

edited

Loading

bigPYJ1151 Aug 18, 2024 •

edited

Loading

zhouyuan commented Sep 9, 2024 •

edited

Loading