Innovations in Data Accuracy and Memory Management for FlashMLA
FlashMLA achieves double optimization of computational efficiency and memory usage by supporting BF16 (Brain Floating Point 16) half-precision computation and advanced paging KV caching mechanism.
BF16 Accuracy Advantage
- Reducing the memory footprint of the 50% while maintaining model accuracy
- Leveraging the BF16 Compute Unit of Hopper GPUs
- Avoiding the numerical overflow problems that tend to occur with traditional FP16s
Paged KV Cache Technology
- Paging block management with fixed 64 size
- Implementing Efficient Memory Allocation for Variable-Length Sequences
- Reduce memory fragmentation to improve cache hit rate
- Supports dynamically adjusted sequence length processing
This answer comes from the articleFlashMLA: Optimizing the MLA Decoding Kernel for Hopper GPUs (DeepSeek Open Source Week Day 1)The
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