FlashDecoding++: Faster Large Language Model Inference on GPUs: Conclusion & References

Table of Links

• Abstract & Introduction
• Backgrounds
• Asynchronized Softmax with Unified Maximum Value
• Flat GEMM Optimization with Double Buffering
• Heuristic Dataflow with Hardware Resource Adaption
• Evaluation
• Related Works
• Conclusion & References

8 Conclusions

We propose FlashDecoding++, a fast Large Language Model inference engine in this paper. FlashDecoding++ accelerates mainstream LLMs with multiple hardware backend support. FlashDecoding++ proposes three novel designs: the asynchronized softmax with unified max value, the flat GEMM optimization with double buffering, and the heuristic dataflow with hardware resource adaption, achieving up to 4.86× and 2.18× speedup on NVIDIA and AMD GPUs compared with Hugging Face implementations. FlashDecoding++ also achieves an average of 1.37× speedup compared with state-of-the-art LLM inference engines, FlashDecoding, on various LLMs.

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