Cuda-graph capturable Dispatch and combine

csrc/host_ir/evaluator.cpp

@@ -472,12 +472,16 @@ void HostIrEvaluator::handle(MoeCombine* combine) {
   auto n_tokens_from_rank =
       getKnownConcreteValue(combine->inTokensFromRank()).as<at::Tensor>();
 
+  auto num_tokens =
+      expr_evaluator_.evaluate(combine->numTokens()).as<int64_t>();
+
   auto result = doMoeCombine(
       x,
       topk_weights,
       src_idx,
       n_tokens_to_rank,
       n_tokens_from_rank,
+      num_tokens,
       communicator_,
       combine->backend());
 

csrc/multidevice/communication.cpp

@@ -341,13 +341,15 @@ MoeCombine::MoeCombine(
     TensorView* in_src_idx,
     TensorView* in_n_tokens_to_rank,
     TensorView* in_n_tokens_from_rank,
+    Val* num_tokens,
     CommunicatorBackend backend)
     : Expr(passkey) {
   addInput(in_x);
   addInput(in_topk_weights);
   addInput(in_src_idx);
   addInput(in_n_tokens_to_rank);
   addInput(in_n_tokens_from_rank);
+  addInput(num_tokens);
   addOutput(out_x);
   addDataAttribute(backend);
   validate();

csrc/multidevice/communication.h

@@ -336,6 +336,7 @@ class MoeCombine : public Expr {
       TensorView* in_src_idx,
       TensorView* in_n_tokens_to_rank,
       TensorView* in_n_tokens_from_rank,
+      Val* num_tokens,
       CommunicatorBackend backend = CommunicatorBackend::kNccl);
 
   MoeCombine(const MoeCombine& other) = delete;
@@ -375,6 +376,17 @@ class MoeCombine : public Expr {
     return input(4)->as<TensorView>();
   }
 
+  //! Extent of the dispatch input's first axis (= original local
+  //! token count T).
+  //!
+  //! Used by the CUDA backend to size recv buffers and the output
+  //! without GPU-to-CPU sync. When pre-allocated outputs are
+  //! supported, the combine output TensorView's shape could be used
+  //! directly instead.
+  Val* numTokens() const {
+    return input(5);
+  }
+
   CommunicatorBackend backend() const {
     return attribute<CommunicatorBackend>(0);
   }

csrc/multidevice/cuda_p2p.cpp

@@ -1457,25 +1457,10 @@ void alltoallvWithCudaBackend(
     const at::Tensor& send,
     const at::Tensor& recv,
     const AlltoallvMetadata& metadata,
-    const std::vector<void*>& recv_ptrs,
+    const at::Tensor& recv_ptrs_gpu,
     CUstream stream) {
   NVF_CHECK(send.is_cuda(), "alltoallv send must be CUDA.");
   NVF_CHECK(recv.is_cuda(), "alltoallv recv must be CUDA.");
-  NVF_CHECK(
-      (int64_t)recv_ptrs.size() == metadata.world_size,
-      "recv_ptrs size must match world size.");
-
-  auto cpu_options = at::TensorOptions().dtype(at::kLong).device(at::kCPU);
-  auto recv_ptrs_cpu = at::empty({metadata.world_size}, cpu_options);
-  auto* ptrs = recv_ptrs_cpu.data_ptr<int64_t>();
-  for (int64_t rank = 0; rank < metadata.world_size; ++rank) {
-    ptrs[rank] =
-        static_cast<int64_t>(reinterpret_cast<uintptr_t>(recv_ptrs[rank]));
-  }
-  auto recv_ptrs_cuda = recv_ptrs_cpu.to(send.device());
-
-  const int64_t elem_stride =
-      metadata.max_send_total > 0 ? send.numel() / metadata.max_send_total : 1;
   NVF_CHECK(
       metadata.max_send_total == 0 ||
           send.numel() % metadata.max_send_total == 0,
@@ -1484,6 +1469,9 @@ void alltoallvWithCudaBackend(
       metadata.max_recv == 0 || recv.numel() % metadata.max_recv == 0,
       "alltoallv recv numel must be divisible by max_recv.");
 
+  const int64_t elem_stride =
+      metadata.max_send_total > 0 ? send.numel() / metadata.max_send_total : 1;
+
   auto send_offsets = metadata.send_offsets;
   auto send_counts = metadata.send_counts;
   auto recv_offsets = metadata.recv_offsets;
@@ -1497,7 +1485,7 @@ void alltoallvWithCudaBackend(
 
   launchAlltoallvKernel(
       send.data_ptr(),
-      reinterpret_cast<const uint64_t*>(recv_ptrs_cuda.data_ptr<int64_t>()),
+      reinterpret_cast<const uint64_t*>(recv_ptrs_gpu.data_ptr<int64_t>()),
       send_offsets.data_ptr<int64_t>(),
       send_counts.data_ptr<int64_t>(),
       recv_offsets.data_ptr<int64_t>(),

csrc/multidevice/cuda_p2p.h

@@ -49,10 +49,14 @@ struct AlltoallvMetadata {
   at::Tensor recv_counts; // CUDA [R]
   at::Tensor send_offsets; // CUDA [R]
   at::Tensor recv_offsets; // CUDA [R]
-  int64_t total_recv = 0;
-  int64_t max_recv = 0;
-  int64_t max_send_total = 0;
-  int64_t max_send_bytes = 0;
+
+  // CPU scalars — upper bounds from the caller, NOT read from GPU.
+  // Using upper bounds (instead of exact GPU values) avoids CPU-GPU
+  // sync and keeps the data path CUDA-graph-capturable.
+  int64_t total_recv = 0; // upper bound on sum(recv_counts)
+  int64_t max_recv = 0; // recv buffer first dim
+  int64_t max_send_total = 0; // send buffer first dim = sum(send_counts)
+  int64_t max_send_bytes = 0; // max per-peer send count (kernel grid X)
   int64_t world_size = 0;
 };
 
@@ -64,7 +68,8 @@ void alltoallvWithCudaBackend(
     const at::Tensor& send,
     const at::Tensor& recv,
     const AlltoallvMetadata& metadata,
-    const std::vector<void*>& recv_ptrs,
+    const at::Tensor& recv_ptrs_gpu, // CUDA [R] int64, from
+                                     // SymmetricTensor::remotePointersTensor
     CUstream stream);
 
 void alltoallvBarrier(const std::string& tag);