Unverified50% confidenceCautionExact time
High-performance attention implementations such as FlashAttention and custom CUDA kernels do not support MPS, making it impossible to run some cutting-edge research code directly on Mac.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
8/25/2026
First Seen
Valid until: 11/23/2026
Sources
Related Entities
Related Claims
Unverified许多第三方库如自定义CUDA kernel、FlashAttention等高性能注意力实现不支持MPS78% similarUnverifiedFlashInfer 是专为 LLM 推理设计的高性能 CUDA 算子库67% similarUnverifiedFlashAttention 的实现需要精通 CUDA 的共享内存管理和线程同步67% similarUnverifiedKDA(Kernel Development Agent)能够自动编写高性能 CUDA 内核,在 MLSys FlashInfer Kernel Contest 中排名第 1 到第 3 位63% similarUnverified新内核通过将量化/反量化操作融合进注意力计算的 CUDA Kernel 中,使 KV 缓存量化不再造成推理减速,某些带宽受限场景下甚至能进一步提升吞吐62% similar
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