Gahow Wang
6da0972740
SGLang-style "write-all, copy-move on acceptance" approach: after tree verification, physically copy an accepted sibling's K/V from its physical cache slot to the canonical sequential position. New CUDA kernel: copy_kv_position_kernel in reshape_and_cache.cu. For one token (src_pos → dst_pos), copies head_dim × num_kv_heads BF16 elements in both K and V pools. Grid = num_kv_heads, block = head_dim. Cost for one token across 36 layers: ~5.3 MB D2D copy @ 900 GB/s = <6μs. Rust FFI: copy_kv_position(k_pool, v_pool, block_ids, src_pos, dst_pos, num_kv_heads, head_dim, block_size, stream). PagedKVCache method: copy_kv_position(slot, src_pos, dst_pos) — uploads block_ids for the sequence, calls the kernel per layer. This is the primitive needed by tree drafting: when a non-primary sibling at cache position P+2 is accepted as the "true" token for target position P+1, call copy_kv_position(slot, P+2, P+1) then truncate to P+2. Next: wire into bench-eagle3 tree drafting loop with top-2 siblings.
37 lines
1.2 KiB
Rust
37 lines
1.2 KiB
Rust
pub mod activation;
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pub mod argmax;
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pub mod attention;
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pub mod dispatch;
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pub mod embedding;
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pub mod gemm;
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pub mod layernorm;
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pub mod moe;
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pub mod quantization;
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pub mod rmsnorm;
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pub mod rope;
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pub mod softmax;
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pub mod transpose;
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pub use activation::{add, bias_add_2d, gelu, gpt_oss_glu, mul, scale, silu, silu_mul};
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pub use argmax::{argmax_bf16_single, argmax_bf16_to_host};
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pub use attention::{
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attention, copy_kv_position, decode_attention, flash_attention, flash_attention_sinks,
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paged_decode_attention, paged_decode_attention_sinks, paged_decode_attention_tree,
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reshape_and_cache_batched_bf16, reshape_and_cache_bf16,
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};
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pub use embedding::{embedding, embedding_device_ids};
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pub use gemm::{GemmBackend, batched_matmul, matmul, matmul_batched_gemv};
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pub use layernorm::layernorm;
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pub use rmsnorm::{add_rmsnorm, rmsnorm};
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pub use rope::{RopeCache, rope_inplace, rope_inplace_device_pos};
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pub use softmax::softmax;
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pub use transpose::{
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merge_heads_gpu, repeat_kv_gpu, reshape_heads_gpu, strided_to_contiguous_gpu,
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transpose_for_rope_gpu, transpose_from_rope_gpu,
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};
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/// Register GPU kernels with the tensor crate. Call once at startup.
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pub fn init() {
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xserv_tensor::register_gpu_contiguous(strided_to_contiguous_gpu);
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}
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