Woosuk Kwon
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c9d5b6d4a8
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Replace FlashAttention with xformers (#70)
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2023-05-05 02:01:08 -07:00 |
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Woosuk Kwon
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436e523bf1
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Refactor attention kernels (#53)
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2023-05-03 13:40:13 -07:00 |
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Woosuk Kwon
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a96d63c21d
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Add support for GPT-NeoX (Pythia) (#50)
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2023-04-28 00:32:10 -07:00 |
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Siyuan (Ryans) Zhuang
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e3cec88aa5
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Memcpy kernel for flash attention (#29)
* optimize
* add benchmark
* add assert
* add test
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2023-04-10 18:22:49 -07:00 |
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Woosuk Kwon
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b9926f7f66
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Support block size 32 (#35)
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2023-04-09 23:07:18 -07:00 |
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Woosuk Kwon
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c267b1a02c
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Add query stride to multi_query_cached_kv_attention & Add kernel benchmark script (#27)
* Add query stride to multi_query_cached_kv_attention
* Add kernel benchmark script
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2023-04-08 13:36:09 -07:00 |
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Woosuk Kwon
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0f40557af6
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Implement block copy kernel to optimize beam search (#32)
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2023-04-07 17:45:07 -07:00 |
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Siyuan (Ryans) Zhuang
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21b3671bbc
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Basic attention kernel that supports cached KV + (multi-)prompts (#24)
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2023-04-04 20:34:46 -07:00 |
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Woosuk Kwon
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897cb2ae28
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Optimize data movement (#20)
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2023-04-02 00:30:17 -07:00 |
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Woosuk Kwon
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09e9245478
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Add custom kernel for RMS normalization (#16)
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2023-04-01 00:51:22 +08:00 |
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Woosuk Kwon
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88c0268a18
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Implement custom kernel for LLaMA rotary embedding (#14)
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2023-03-30 11:04:21 -07:00 |
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Woosuk Kwon
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a1b3de86cd
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Refactor the test code for attention kernels (#13)
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2023-03-29 18:59:27 -07:00 |
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Woosuk Kwon
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3e9f991d6a
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Use FlashAttention for multi_query_kv_attention (#4)
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2023-03-01 21:13:08 -08:00 |
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Woosuk Kwon
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0deacbce6e
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Implement single_query_cached_kv_attention kernel (#3)
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2023-03-01 15:02:19 -08:00 |
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