"""JIT TMA bulk-store path for ``set_mla_kv_buffer``. Each warp scatter-writes one item's (nope, rope) row via a single ``cp.async.bulk.global.shared::cta`` store. Requires SM90+ (Hopper or later) for the TMA bulk-store hardware. The host-side wrapper in ``sglang.srt.mem_cache.utils`` falls back to a Triton kernel for older arches. """ from __future__ import annotations import logging from typing import TYPE_CHECKING import torch from sglang.jit_kernel.utils import ( cache_once, is_arch_support_pdl, load_jit, make_cpp_args, ) if TYPE_CHECKING: from tvm_ffi.module import Module logger = logging.getLogger(__name__) @cache_once def _jit_set_mla_kv_buffer_module( nope_bytes: int, rope_bytes: int, use_pdl: bool ) -> Module: args = make_cpp_args(nope_bytes, rope_bytes, use_pdl) return load_jit( f"set_mla_kv_buffer_{nope_bytes}_{rope_bytes}", *args, cuda_files=["elementwise/set_mla_kv_buffer.cuh"], cuda_wrappers=[ ("set_mla_kv_buffer", f"SetMlaKVBufferKernel<{args}>::run"), ], ) @cache_once def can_use_set_mla_kv_buffer(nope_bytes: int, rope_bytes: int) -> bool: """Whether the TMA path can be used for these row byte widths. TMA bulk store requires ``(nope_bytes + rope_bytes)`` to be a multiple of 16; both halves individually must also be a multiple of 4 (the warp-coop smem load lower bound). """ if nope_bytes % 4 != 0 or rope_bytes % 4 != 0: logger.warning( "Unsupported nope_bytes=%d rope_bytes=%d for JIT set_mla_kv_buffer:" " both must be multiples of 4", nope_bytes, rope_bytes, ) return False if (nope_bytes + rope_bytes) % 16 != 0: logger.warning( "Unsupported nope_bytes=%d rope_bytes=%d for JIT set_mla_kv_buffer:" " (nope_bytes + rope_bytes) must be a multiple of 16 for TMA bulk store", nope_bytes, rope_bytes, ) return False try: _jit_set_mla_kv_buffer_module(nope_bytes, rope_bytes, is_arch_support_pdl()) return True except Exception as e: # pragma: no cover - compile-time only logger.warning( "Failed to load JIT set_mla_kv_buffer kernel " "with nope_bytes=%d rope_bytes=%d: %s", nope_bytes, rope_bytes, e, ) return False def _pick_num_warps(n_loc: int) -> int: # Tuned on GB300: nw=4 wins below 1024 (more CTAs spread across SMs); # nw=8 wins above (each CTA amortises the bulk-group commit better). return 4 if n_loc <= 768 else 8 def set_mla_kv_buffer( kv_buffer: torch.Tensor, loc: torch.Tensor, cache_k_nope: torch.Tensor, cache_k_rope: torch.Tensor, num_warps: int = 0, ) -> None: """Write packed [k_nope | k_rope] rows into ``kv_buffer`` at ``loc`` indices via a TMA bulk-store. SM90+ only — the caller is expected to gate. Shapes (last dim is treated as the row payload; any leading singleton dims on the source tensors are flattened away): kv_buffer: [num_pages, total_dim] or [num_pages, 1, total_dim] cache_k_nope: [n_loc, nope_dim] or [n_loc, 1, nope_dim] cache_k_rope: [n_loc, rope_dim] or [n_loc, 1, rope_dim] loc: [n_loc] """ n_loc = loc.shape[0] if n_loc == 0: return src_nope = cache_k_nope.view(n_loc, -1) if cache_k_nope.dim() != 2 else cache_k_nope src_rope = cache_k_rope.view(n_loc, -1) if cache_k_rope.dim() != 2 else cache_k_rope buf = kv_buffer.view(kv_buffer.shape[0], -1) if kv_buffer.dim() != 2 else kv_buffer nope_bytes = src_nope.shape[-1] * src_nope.element_size() rope_bytes = src_rope.shape[-1] * src_rope.element_size() if num_warps <= 0: num_warps = _pick_num_warps(n_loc) module = _jit_set_mla_kv_buffer_module( nope_bytes, rope_bytes, is_arch_support_pdl() ) module.set_mla_kv_buffer(buf, loc, src_nope, src_rope, num_warps)