[CUDA] Reduce use of managed memory (#2725)

* Use async cuda malloc managed with cuda 13

* add pool threshold

* refactor for regular cuda malloc

* load eval gpu for cuda

* remove use of cuda pool, use cuda free async

* fix

* fix

* fix

* fix

* fix + comment

mlx/backend/cuda/cudnn_utils.h

@@ -3,6 +3,7 @@
 #pragma once
 
 #include "mlx/array.h"
+#include "mlx/backend/cuda/allocator.h"
 #include "mlx/backend/cuda/device/config.h"
 #include "mlx/backend/cuda/utils.h"
 #include "mlx/dtype_utils.h"
@@ -23,7 +24,7 @@ class CommandEncoder;
 // Return pointer alignment of |x|'s data.
 inline uint8_t get_alignment(const array& x) {
   uint8_t alignment = 1;
-  uintptr_t address = reinterpret_cast<uintptr_t>(x.data<void>());
+  uintptr_t address = reinterpret_cast<uintptr_t>(gpu_ptr<void>(x));
   for (; alignment < 32; alignment *= 2) {
     if (address % (alignment * 2)) {
       return alignment;
@@ -56,7 +57,7 @@ inline std::array<T, MAX_NDIM> vector_key(const Vec<T>& vec) {
 
 // Helpers used by get_data_ptrs to get pointers.
 inline void* get_data_ptr(const array& arr) {
-  return const_cast<void*>(arr.data<void>());
+  return const_cast<void*>(gpu_ptr<void>(arr));
 }
 
 template <typename T, typename = std::enable_if_t<std::is_scalar_v<T>>>