Fuse split rotary for Group Query Attention #940
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CC @masahi as the original author of this optimization :) |
| @@ -70,10 +70,84 @@ def split_rotary( | |||
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| return split_rotary | |||
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| def get_split_rotary_group_query_attention(num_query_heads, num_kv_heads, head_dim, position_embedding_base): | |||
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I’m wondering if we can merge the two get_split_rotary into one.
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We fuse split rotary of GQA into 2 kernels because of num_heads are different, while split rotary of non-GQA is fused into 1 kernel. So let's keep them as different function
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nice, does a big model that use MQA / GQA benefit from this pass? The speed up for 13B was much smaller than 7B when I tested. |
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llama2 70b uses GQA. Indeed the speed up is small. Only 2% I observed |
MasterJH5574
approved these changes
Sep 19, 2023
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