* Instead of allocating UserBuffers at beginning of runtime, UB buffers
are now managed with global allocator. The allocator will dynamically
assign free UB buffer or allocate new buffer for torch tensor. It makes
userbuffers easier to use.
* In common usecase, the Userbuffers will be allocated correctly during
warm up stage. There is no dynamic allocation during inference.
* UB fusion pattern is rewroten using the new UB Allocator. It contains
following passes:
1. Fuse Quant with allreduce, replace with UB impl, and insert a
copy_to_userbuffers. Currently the normal allreduce still does not
support FP8 quant. So this need to be done in UB pass
2. Convert all supported allreduce with UB and insert copy_to_userbuffers.
3. Fuse op before ar with the copy_to_userbuffers. So the op directly
writes to the userbuffer
4. Remove userbuffers finalize if the output is connect to another UB
allreduce.
Signed-off-by: Jin Li <59594262+liji-nv@users.noreply.github.com>
* Reapply "refactor: Replace DecoderFinishedEvent with CudaEvent in decoder clas…" (#3183)
This reverts commit 75495730bc.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* fixup! Reapply "refactor: Replace DecoderFinishedEvent with CudaEvent in decoder clas…" (#3183)
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Simplifiy disableLookahead method
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* Update DecoderBuffers comments
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Move numDecodingEngineTokens to DecoderState
This commit introduces new methods in the DecoderState class to manage the number of tokens for each request in a batch. The following changes were made:
- Added `getNumDecodingEngineTokens()` to retrieve the number of tokens for all requests.
- Added `getNumDecodingEngineTokens(SizeType32 batchIdx)` to get the token count for a specific request.
- Added `setNumDecodingEngineTokens(SizeType32 batchIdx, SizeType32 numTokens)` to set the token count for a specific request.
- Updated the setup method to initialize the token count vector based on the maximum batch size.
- Refactored the `CreateNewDecoderRequests` class to utilize the new token management methods, improving clarity and maintainability.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Improve shape variables in DecoderState
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
- Updated the `forwardAsync` method in `GptDecoderBatched` and `iGptDecoderBatched` to return `CudaEvent` instead of `DecoderFinishedEventPtr`, simplifying event handling.
- Removed the `DecoderFinishedEvent` class and its associated usage across various files, streamlining the codebase.
- Adjusted related methods and Python bindings to accommodate the new event structure, ensuring compatibility and maintaining functionality.
These changes enhance the clarity and efficiency of the decoding process in the batch manager.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Update gatherTree function to accept CUDA stream parameter
This commit modifies the gatherTree function signature to include a runtime::CudaStream parameter, enhancing flexibility in stream management. Additionally, it removes unnecessary buffer manager parameters and stream handling from the function, streamlining the code. The finalize method in GptDecoderBatched is also updated to reflect these changes, improving clarity and maintainability in the decoding process.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Update GptDecoderBatched finalize
This commit refactors the GptDecoderBatched class to improve method signatures and reduce code complexity:
- Modified finalize method to accept DecoderState as a parameter
- Updated method signatures to work with the new DecoderState approach
- Improved code organization and readability
The changes continue the ongoing refactoring to centralize decoder state management and simplify the decoder implementation.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Remove ForwardType enum from GptDecoderBatched
- Remove ForwardType enum from GptDecoderBatched
- Simplify forwardDispatch and forwardDecoder methods
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Remove forwardDecoder method from GptDecoderBatched
- Eliminate the forwardDecoder method to streamline the decoding process.
- Update forwardDispatch to directly call forwardAsync when input batch size is greater than zero.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Move event handling from forwardDispatch to forwardAsync
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
