From f9e1a141352207f4fea7ee4c212b52107c8b79d7 Mon Sep 17 00:00:00 2001
From: Awni Hannun <awni@apple.com>
Date: Thu, 20 Nov 2025 07:27:50 -0800
Subject: [PATCH] [CUDA] Partly fix random for large sizes (#2798)

---
 mlx/backend/cuda/random.cu | 26 ++++++++++++++++----------
 1 file changed, 16 insertions(+), 10 deletions(-)

diff --git a/mlx/backend/cuda/random.cu b/mlx/backend/cuda/random.cu
index 10171ff28..6b323e79e 100644
--- a/mlx/backend/cuda/random.cu
+++ b/mlx/backend/cuda/random.cu
@@ -139,10 +139,10 @@ void RandomBits::eval_gpu(const std::vector<array>& inputs, array& out) {
   // keys has shape (N1, ..., NK, 2)
   // out has shape (N1, ..., NK, M1, M2, ...)
   auto& keys = inputs[0];
-  uint32_t num_keys = keys.size() / 2;
+  size_t num_keys = keys.size() / 2;
 
-  uint32_t elems_per_key = out.size() / num_keys;
-  uint32_t bytes_per_key = out.itemsize() * elems_per_key;
+  size_t elems_per_key = out.size() / num_keys;
+  size_t bytes_per_key = out.itemsize() * elems_per_key;
   auto& s = stream();
   auto& encoder = cu::get_command_encoder(s);
   out.set_data(cu::malloc_async(out.nbytes(), encoder));
@@ -150,19 +150,25 @@ void RandomBits::eval_gpu(const std::vector<array>& inputs, array& out) {
     return;
   }
 
-  uint32_t out_per_key = (bytes_per_key + 4 - 1) / 4;
-  uint32_t half_size = out_per_key / 2;
+  size_t out_per_key = (bytes_per_key + 4 - 1) / 4;
+  size_t half_size = out_per_key / 2;
+
   bool odd = out_per_key % 2;
+  if ((half_size + odd) >= UINT32_MAX || num_keys >= UINT32_MAX) {
+    throw std::runtime_error("[RandomBits::eval_gpu] Large size unsupported");
+  }
 
   encoder.set_input_array(keys);
   encoder.set_output_array(out);
-  dim3 grid_dims{num_keys, half_size + odd};
-  int64_t total = grid_dims.x * grid_dims.y;
-  int32_t threads_y = 1;
-  while ((total / threads_y) >= (1U << 31)) {
+  int64_t total = num_keys * (half_size + odd);
+  uint32_t threads_y = 1;
+  while ((total / threads_y) >= UINT_MAX) {
     threads_y *= 2;
   }
-  int32_t threads_x = cuda::ceil_div(total, threads_y);
+  uint32_t threads_x = cuda::ceil_div(total, threads_y);
+
+  dim3 grid_dims{
+      static_cast<uint32_t>(num_keys), static_cast<uint32_t>(half_size + odd)};
   auto [grid, block] = get_grid_and_block(threads_x, threads_y, 1);
   auto& stream = encoder.stream();
   if (keys.flags().row_contiguous) {