Improve parallelism in RoPE with pos_ids #609
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The previous kernel was not parallelised sufficiently well for low batch sizes. Similarly to the regular rotary kernel, now all qo/kv heads are split across separate blocks. In decode mode, the pos_ids kernel is now faster.
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Hi @nandor we use such parallelism mainly to save sin/cos computation time (same sin/cos can be reused for multiple heads). Would you mind running https://github.com/flashinfer-ai/flashinfer/blob/32d9510d67187f1f3a379cce81302cdd15a557d2/benchmarks/bench_rope.py ? |
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You are right - saving Unfortunately this sort of batching is a bit more convoluted to implement in CUDA than triton and internally we'll be relying on a Triton kernel instead. |
yzh119
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Nov 14, 2024
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Sound good, thank you!
this sort of batching is a bit more convoluted to implement in CUDA than triton and internally we'll be relying on a Triton kernel instead.
Yes I agree, we plan to port most of the kernels (except for sampling and attention) to triton in v0.2.1 :)
james-p-xu
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Nov 16, 2024
flashinfer-ai/flashinfer#609 potentially introduces correctness issues
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I'm actually seeing that this change causes a correctness issue wrt apply_rope_pos_ids. Here's a sample comparison script, passing prior to this commit hash (32d9510) but failing post-change: https://github.com/sgl-project/sglang/blob/dd0d2a3af4967880362e3bad9d95cd14572c89ea/scripts/playground/compare_flashinfer_vllm_rope.py |
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@james-p-xu I'll fix it, thank you! |
yzh119
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Nov 20, 2024
As observed by @james-p-xu, #609 produce wrong results for some input shapes, this PR fixes the correctness issue, and add optimizations of dispatching to different parallelism modes for different input shapes. For large shape inputs, using the original implementation (re-use sin/cos for different heads) will be better. For small shape inputs, using head parallelism will be better. Some results: ``` Before #609 (no head-parallelism, re-use sin/cos value) ----------------- batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 27us, throughput: 0.762GB/s batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 22us, throughput: 0.919GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 27us, throughput: 95.699GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 28us, throughput: 95.244GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 31us, throughput: 670.254GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 31us, throughput: 667.253GB/s --- batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 27us, throughput: 14.490GB/s batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 27us, throughput: 14.466GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 37us, throughput: 1344.086GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 37us, throughput: 1344.902GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 148us, throughput: 2699.475GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 147us, throughput: 2701.897GB/s --- batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 27us, throughput: 74.322GB/s batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 27us, throughput: 74.568GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 110us, throughput: 2352.352GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 110us, throughput: 2365.580GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 718us, throughput: 2893.608GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 717us, throughput: 2894.859GB/s --- batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 27us, throughput: 95.373GB/s batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 27us, throughput: 95.810GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 130us, throughput: 2583.872GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 129us, throughput: 2595.944GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 923us, throughput: 2907.408GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 924us, throughput: 2905.533GB/s Head parallelism only (no dispatch) --------------------- batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 6us, throughput: 3.321GB/s batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 6us, throughput: 3.391GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 358.862GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 362.361GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 15us, throughput: 1413.175GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 15us, throughput: 1437.332GB/s --- batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 6us, throughput: 60.526GB/s batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 6us, throughput: 60.127GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 26us, throughput: 1897.923GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 24us, throughput: 2050.075GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 164us, throughput: 2431.650GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 147us, throughput: 2709.333GB/s --- batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 284.641GB/s batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 302.815GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 109us, throughput: 2391.712GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 97us, throughput: 2671.150GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 860us, throughput: 2413.211GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 828us, throughput: 2508.817GB/s --- batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 349.795GB/s batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 376.624GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 139us, throughput: 2413.690GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 124us, throughput: 2705.994GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 1110us, throughput: 2417.480GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 1063us, throughput: 2525.976GB/s This PR (shape dispatch) --------------------- batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 28us, throughput: 0.728GB/s batch_size: 1, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 6us, throughput: 3.451GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 359.759GB/s batch_size: 1, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 361.286GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 15us, throughput: 1426.267GB/s batch_size: 1, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 15us, throughput: 1433.691GB/s --- batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 6us, throughput: 60.390GB/s batch_size: 19, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 6us, throughput: 59.937GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 26us, throughput: 1892.575GB/s batch_size: 19, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 24us, throughput: 2049.735GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 148us, throughput: 2698.780GB/s batch_size: 19, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 147us, throughput: 2701.558GB/s --- batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 285.335GB/s batch_size: 99, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 303.373GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 110us, throughput: 2351.126GB/s batch_size: 99, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 110us, throughput: 2362.898GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 717us, throughput: 2893.713GB/s batch_size: 99, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 717us, throughput: 2894.902GB/s --- batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 7us, throughput: 350.720GB/s batch_size: 128, append_len: 1, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 7us, throughput: 376.690GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 130us, throughput: 2584.221GB/s batch_size: 128, append_len: 128, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 129us, throughput: 2596.612GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: False, latency: 924us, throughput: 2906.480GB/s batch_size: 128, append_len: 1024, num_qo_heads: 32, num_kv_heads: 8, head_dim: 128, use_cos_sin_cache: True, latency: 924us, throughput: 2905.134GB/s ``` cc @nandor @james-p-xu
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The previous kernel was not parallelised sufficiently well for low batch sizes. Similarly to the regular rotary kernel, now all qo/kv heads are split across separate blocks.
In decode mode, the pos_ids kernel is now faster.