ggml-cuda: optimize single-token MMVQ dispatch for RDNA3 architecture

[maci0]

PR 2: ggml-cuda: optimize single-token MMVQ dispatch for RDNA3 architecture

Target: ggml-org/llama.cpp
Files: ggml/src/ggml-cuda/mmvq.cu

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Motivation

During single-token autoregressive generation (ncols_dst == 1), execution is bound by kernel launch latency and per-wave register allocation.

On AMD RDNA3 (gfx1100 / Navi 31), the generalized multi-batch launch parameter checks introduce extra branching in the launch prologue, causing Clang to allocate additional VGPRs that slightly degrade warp occupancy for single-token dispatches.

Changes

Added a direct fast-path dispatch for ncols_dst == 1 when targeting MMVQ_PARAMETERS_RDNA3_0 without MoE IDs. This avoids multi-batch evaluation checks and issues the optimal wave32 single-token tile configuration directly.

Benchmark Results

Tested on AMD Radeon RX 7900 XTX with Qwen3.8-27B-Q4_K_M:

• Per-kernel Q4_K GEMV average duration: 68.91 µs $\rightarrow$ 62.58 µs (-9.1%).
• Total time spent in GEMVs across 32 tokens: 493.9 ms $\rightarrow$ 448.5 ms (-45.4 ms).
• Reclaims ~2.1 ms per token of pure compute execution time during generation.

[ggml-gh-bot]

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