1 files changed, 23 insertions, 28 deletions

diff --git a/lib/THC/generic/THCTensorMath.cu b/lib/THC/generic/THCTensorMath.cu
index 4c609ba..0eed5a9 100644
--- a/lib/THC/generic/THCTensorMath.cu
+++ b/lib/THC/generic/THCTensorMath.cu
@@ -175,23 +175,9 @@ void THCTensor_(catArray)(THCState *state, THCTensor *result,
     real *data = THCTensor_(data)(state, result);
 
     // Kernel Parameter
-    CatArrInputTensor<real, unsigned int> stackInputs[CAT_ARRAY_BATCH_SIZE];
-    CatArrInputTensor<real, unsigned int> *d_inputs;
-
-    // Attempt to re-use stream's scratch space for the input metadata
-    bool usedScratch = false;
     size_t tensorMetadataSize = sizeof(CatArrInputTensor<real, unsigned int>) * CAT_ARRAY_BATCH_SIZE;
-    if (THCState_getCurrentDeviceScratchSpaceSize(state) > tensorMetadataSize) {
-      void* space = THCState_getCurrentDeviceScratchSpace(state);
-      if (space) {
-        d_inputs = (CatArrInputTensor<real, unsigned int> *) space;
-        usedScratch = true;
-      }
-    }
-    if (!usedScratch) {
-      // Fallback to allocating GPU memory
-      THCudaCheck(THCudaMalloc(state, (void**) &d_inputs, tensorMetadataSize));
-    }
+    CatArrInputTensor<real, unsigned int> *d_inputs;
+    THCudaCheck(THCudaMalloc(state, (void**) &d_inputs, tensorMetadataSize));
 
     OutputTensorSizeStride<unsigned int, CAT_ARRAY_MAX_INPUT_DIMS> param;
 
@@ -201,13 +187,17 @@ void THCTensor_(catArray)(THCState *state, THCTensor *result,
       param.outputStride[i] = THCTensor_(stride)(state, result, i);
     }
 
+    THCStream* stream = THCState_getStream(state);
+
     // Template Declarations for dim = 1, 2, 3, 4
 #define HANDLE_CASE(DIMS) \
-  CatArrayBatchedCopy<real, unsigned int, DIMS><<<applyGrid, applyBlock, 0, THCState_getCurrentStream(state)>>>(data, d_inputs, param, cat_dimension, param.outputStride[cat_dimension]);
+  CatArrayBatchedCopy<real, unsigned int, DIMS><<<applyGrid, applyBlock, 0, stream->stream>>>(data, d_inputs, param, cat_dimension, param.outputStride[cat_dimension]);
 
     // Now we loop
     offset = 0;
     for (i = 0; i < numInputs; i += CAT_ARRAY_BATCH_SIZE) {
+      // Re-allocate stackInputs every iteration to avoid read-after-write hazard
+      CatArrInputTensor<real, unsigned int>* stackInputs = (CatArrInputTensor<real, unsigned int>*) THCudaHostAlloc(state, tensorMetadataSize);
       cohortMax = 0;
       for (j = 0; j < CAT_ARRAY_BATCH_SIZE && (i+j) < numInputs; ++j) {
         long dimSize = cat_dimension < THCTensor_(nDimension)(state, inputs[i+j])
@@ -223,7 +213,14 @@ void THCTensor_(catArray)(THCState *state, THCTensor *result,
         // update offset
         offset += dimSize;
       }
-      THCudaCheck(cudaMemcpy(d_inputs, stackInputs, j * sizeof(CatArrInputTensor<real, unsigned int>), cudaMemcpyHostToDevice));
+      THCudaCheck(cudaMemcpyAsync(
+          d_inputs,
+          stackInputs,
+          j * sizeof(CatArrInputTensor<real, unsigned int>),
+          cudaMemcpyHostToDevice,
+          stream->stream));
+      THCudaHostRecord(state, stackInputs);
+      THCudaHostFree(state, stackInputs);
 
       // Next, let's consider how we set our kernel launch parameters.
       // We borrow from THCApply, which the kernel's internal indexing
@@ -256,9 +253,7 @@ void THCTensor_(catArray)(THCState *state, THCTensor *result,
       }
       THCudaCheck(cudaGetLastError());
     }
-    if (!usedScratch) {
-      THCudaCheck(THCudaFree(state, (void *)d_inputs));
-    }
+    THCudaCheck(THCudaFree(state, d_inputs));
 #undef HANDLE_CASE
   } else {
     offset = 0;
@@ -399,10 +394,10 @@ void THCTensor_(linspace)(THCState *state, THCTensor *r_, real a, real b, long n
   if (THCTensor_(nElement)(state, r_) != n) THCTensor_(resize1d)(state, r_, n);
   if (n == 1) THCTensor_(fill)(state, r_, a);
   else {
-    THCTensor *r = THCTensor_(isContiguous)(state, r_) 
+    THCTensor *r = THCTensor_(isContiguous)(state, r_)
                    ? r_ // if r_ is contiguous we can direct work on it
                    : THCTensor_(newContiguous)(state, r_);
-    real step = THCNumerics<real>::div(THCNumerics<real>::sub(b, a), 
+    real step = THCNumerics<real>::div(THCNumerics<real>::sub(b, a),
                                        ScalarConvert<long,real>::to(n - 1));
     LinspaceOp<real> linspace_method(a, step);
     thrust::device_ptr<real> data_(THCTensor_(data)(state, r));
@@ -420,10 +415,10 @@ void THCTensor_(logspace)(THCState *state, THCTensor *r_, real a, real b, long n
   if (THCTensor_(nElement)(state, r_) != n) THCTensor_(resize1d)(state, r_, n);
   if (n == 1) THCTensor_(fill)(state, r_, THCNumerics<real>::exp10(a));
   else {
-    THCTensor *r = THCTensor_(isContiguous)(state, r_) 
-                   ? r_ 
+    THCTensor *r = THCTensor_(isContiguous)(state, r_)
+                   ? r_
                    : THCTensor_(newContiguous)(state, r_);
-    real step = THCNumerics<real>::div(THCNumerics<real>::sub(b, a), 
+    real step = THCNumerics<real>::div(THCNumerics<real>::sub(b, a),
                                        ScalarConvert<long,real>::to(n - 1));
     LogspaceOp<real> logspace_method(a, step);
     thrust::device_ptr<real> data_(THCTensor_(data)(state, r));
@@ -444,8 +439,8 @@ void THCTensor_(range)(THCState *state, THCTensor *r_, accreal xmin, accreal xma
               , 2, "upper bound and larger bound incoherent with step sign");
   ptrdiff_t size = (ptrdiff_t) (((xmax - xmin) / step) + 1);
   if (THCTensor_(nElement)(state, r_) != size) THCTensor_(resize1d)(state, r_, size);
-  THCTensor *r = THCTensor_(isContiguous)(state, r_) 
-                 ? r_ 
+  THCTensor *r = THCTensor_(isContiguous)(state, r_)
+                 ? r_
                  : THCTensor_(newContiguous)(state, r_);
   LinspaceOp<real,accreal> linspace_method(xmin, step);
   thrust::device_ptr<real> data_(THCTensor_(data)(state, r));