[None][feat] retune causalConv1d fwd dispatch for varlen and short sequences (NVIDIA#12739)

Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com>

Author: nv-guomingz

cpp/tensorrt_llm/kernels/causalConv1d/causalConv1d.cu

@@ -4,7 +4,7 @@
  * and https://github.com/Dao-AILab/causal-conv1d/blob/main/csrc/causal_conv1d_update.cu
  * Copyright (c) 2024, Tri Dao.
  *
- * Copyright (c) 2022-2025, NVIDIA CORPORATION.  All rights reserved.
+ * Copyright (c) 2022-2026, NVIDIA CORPORATION.  All rights reserved.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -349,20 +349,45 @@ void causal_conv1d_fwd_launch(ConvParamsBase& params, cudaStream_t stream)
         });
 }
 
+template <int kWidth, typename input_t, typename weight_t>
+void causal_conv1d_fwd_dispatch(ConvParamsBase& params, cudaStream_t stream)
+{
+    bool const isVarlen = params.query_start_loc_ptr != nullptr;
+    constexpr int kNarrowThreads = 64;
+    constexpr int kWideThreads = 128;
+    constexpr int kNElts = sizeof(input_t) == 4 ? 4 : 8;
+    constexpr int kShortSeqThreshold = kNarrowThreads * kNElts;
+    // Varlen prefill launches one block per sequence/channel pair, so the per-sequence
+    // work is usually much smaller than params.seqlen suggests. That path also disables
+    // the wide vector-load specialization, so the 128-thread kernel tends to overprovision
+    // threads for many short chunks. Prefer the narrower launch for varlen and for short
+    // fixed-length inputs; keep the wider launch for long dense sequences.
+    bool const preferNarrowKernel = isVarlen || params.seqlen <= kShortSeqThreshold;
+
+    if (preferNarrowKernel)
+    {
+        causal_conv1d_fwd_launch<kNarrowThreads, kWidth, input_t, weight_t>(params, stream);
+    }
+    else
+    {
+        causal_conv1d_fwd_launch<kWideThreads, kWidth, input_t, weight_t>(params, stream);
+    }
+}
+
 template <typename input_t, typename weight_t>
 void causal_conv1d_fwd_cuda(ConvParamsBase& params, cudaStream_t stream)
 {
     if (params.width == 2)
     {
-        causal_conv1d_fwd_launch<128, 2, input_t, weight_t>(params, stream);
+        causal_conv1d_fwd_dispatch<2, input_t, weight_t>(params, stream);
     }
     else if (params.width == 3)
     {
-        causal_conv1d_fwd_launch<128, 3, input_t, weight_t>(params, stream);
+        causal_conv1d_fwd_dispatch<3, input_t, weight_t>(params, stream);
     }
     else if (params.width == 4)
     {
-        causal_conv1d_fwd_launch<128, 4, input_t, weight_t>(params, stream);
+        causal_conv1d_fwd_dispatch<4, input_t, weight_t>(params, stream);
     }
 }