Optimize sorting of non-uniformly distributed data (#3383)

* Optimized CudaSort for non-uniformly distributed data

* Optimized OpenCLSort for non-uniformly distributed data

* Further tuned distributing elements between buckets

* Copied optimizations over to OpenCL

platforms/cuda/include/CudaSort.h

@@ -9,7 +9,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2010-2018 Stanford University and the Authors.      *
+ * Portions copyright (c) 2010-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -77,8 +77,12 @@ public:
      *                   on the heap with the "new" operator.  This object takes over ownership of it,
      *                   and deletes it when the CudaSort is deleted.
      * @param length     the length of the arrays this object will be used to sort
+     * @param uniform    whether the input data is expected to follow a uniform or nonuniform
+     *                   distribution.  This argument is used only as a hint.  It allows parts
+     *                   of the algorithm to be tuned for faster performance on the expected
+     *                   distribution.
      */
-    CudaSort(CudaContext& context, SortTrait* trait, unsigned int length);
+    CudaSort(CudaContext& context, SortTrait* trait, unsigned int length, bool uniform=true);
     ~CudaSort();
     /**
      * Sort an array.
@@ -94,7 +98,7 @@ private:
     CudaArray buckets;
     CUfunction shortListKernel, shortList2Kernel, computeRangeKernel, assignElementsKernel, computeBucketPositionsKernel, copyToBucketsKernel, sortBucketsKernel;
     unsigned int dataLength, rangeKernelSize, positionsKernelSize, sortKernelSize;
-    bool isShortList;
+    bool isShortList, uniform;
 };
 
 /**

platforms/cuda/src/CudaNonbondedUtilities.cpp

@@ -279,7 +279,7 @@ void CudaNonbondedUtilities::initialize(const System& system) {
         sortedBlockBoundingBox.initialize(context, numAtomBlocks+1, 4*elementSize, "sortedBlockBoundingBox");
         oldPositions.initialize(context, numAtoms, 4*elementSize, "oldPositions");
         rebuildNeighborList.initialize<int>(context, 1, "rebuildNeighborList");
-        blockSorter = new CudaSort(context, new BlockSortTrait(context.getUseDoublePrecision()), numAtomBlocks);
+        blockSorter = new CudaSort(context, new BlockSortTrait(context.getUseDoublePrecision()), numAtomBlocks, false);
         vector<unsigned int> count(2, 0);
         interactionCount.upload(count);
         rebuildNeighborList.upload(&count[0]);

platforms/cuda/src/CudaSort.cpp

@@ -6,7 +6,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2010-2018 Stanford University and the Authors.      *
+ * Portions copyright (c) 2010-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -32,7 +32,8 @@
 using namespace OpenMM;
 using namespace std;
 
-CudaSort::CudaSort(CudaContext& context, SortTrait* trait, unsigned int length) : context(context), trait(trait), dataLength(length) {
+CudaSort::CudaSort(CudaContext& context, SortTrait* trait, unsigned int length, bool uniform) :
+        context(context), trait(trait), dataLength(length), uniform(uniform) {
     // Create kernels.
 
     map<string, string> replacements;
@@ -42,11 +43,12 @@ CudaSort::CudaSort(CudaContext& context, SortTrait* trait, unsigned int length)
     replacements["MIN_KEY"] = trait->getMinKey();
     replacements["MAX_KEY"] = trait->getMaxKey();
     replacements["MAX_VALUE"] = trait->getMaxValue();
+    replacements["UNIFORM"] = (uniform ? "1" : "0");
     CUmodule module = context.createModule(context.replaceStrings(CudaKernelSources::sort, replacements));
     shortListKernel = context.getKernel(module, "sortShortList");
     shortList2Kernel = context.getKernel(module, "sortShortList2");
     computeRangeKernel = context.getKernel(module, "computeRange");
-    assignElementsKernel = context.getKernel(module, "assignElementsToBuckets");
+    assignElementsKernel = context.getKernel(module, uniform ? "assignElementsToBuckets" : "assignElementsToBuckets2");
     computeBucketPositionsKernel = context.getKernel(module, "computeBucketPositions");
     copyToBucketsKernel = context.getKernel(module, "copyDataToBuckets");
     sortBucketsKernel = context.getKernel(module, "sortBuckets");

platforms/cuda/src/kernels/sort.cu

@@ -79,6 +79,7 @@ __global__ void sortShortList2(const DATA_TYPE* __restrict__ dataIn, DATA_TYPE*
  */
 __global__ void computeRange(const DATA_TYPE* __restrict__ data, unsigned int length, KEY_TYPE* __restrict__ range,
         unsigned int numBuckets, unsigned int* __restrict__ bucketOffset) {
+#if UNIFORM
     extern __shared__ KEY_TYPE minBuffer[];
     KEY_TYPE* maxBuffer = minBuffer+blockDim.x;
     KEY_TYPE minimum = MAX_KEY;
@@ -110,7 +111,8 @@ __global__ void computeRange(const DATA_TYPE* __restrict__ data, unsigned int le
         range[0] = minimum;
         range[1] = maximum;
     }
-    
+#endif
+
     // Clear the bucket counters in preparation for the next kernel.
 
     for (unsigned int index = threadIdx.x; index < numBuckets; index += blockDim.x)
@@ -118,7 +120,7 @@ __global__ void computeRange(const DATA_TYPE* __restrict__ data, unsigned int le
 }
 
 /**
- * Assign elements to buckets.
+ * Assign elements to buckets.  This version is optimized for uniformly distributed data.
  */
 __global__ void assignElementsToBuckets(const DATA_TYPE* __restrict__ data, unsigned int length, unsigned int numBuckets, const KEY_TYPE* __restrict__ range,
         unsigned int* __restrict__ bucketOffset, unsigned int* __restrict__ bucketOfElement, unsigned int* __restrict__ offsetInBucket) {
@@ -133,6 +135,85 @@ __global__ void assignElementsToBuckets(const DATA_TYPE* __restrict__ data, unsi
     }
 }
 
+/**
+ * Assign elements to buckets.  This version is optimized for non-uniformly distributed data.
+ */
+__global__ void assignElementsToBuckets2(const DATA_TYPE* __restrict__ data, unsigned int length, unsigned int numBuckets, const KEY_TYPE* __restrict__ range,
+        unsigned int* __restrict__ bucketOffset, unsigned int* __restrict__ bucketOfElement, unsigned int* __restrict__ offsetInBucket) {
+    // Load 64 datapoints and sort them to get an estimate of the data distribution.
+
+    __shared__ KEY_TYPE elements[64];
+    if (threadIdx.x < 64) {
+        int index = (int) (threadIdx.x*length/64.0);
+        elements[threadIdx.x] = getValue(data[index]);
+    }
+    __syncthreads();
+    for (unsigned int k = 2; k <= 64; k *= 2) {
+        for (unsigned int j = k/2; j > 0; j /= 2) {
+            if (threadIdx.x < 64) {
+                int ixj = threadIdx.x^j;
+                if (ixj > threadIdx.x) {
+                    KEY_TYPE value1 = elements[threadIdx.x];
+                    KEY_TYPE value2 = elements[ixj];
+                    bool ascending = (threadIdx.x&k) == 0;
+                    KEY_TYPE lowKey = (ascending ? value1 : value2);
+                    KEY_TYPE highKey = (ascending ? value2 : value1);
+                    if (lowKey > highKey) {
+                        elements[threadIdx.x] = value2;
+                        elements[ixj] = value1;
+                    }
+                }
+            }
+            __syncthreads();
+        }
+    }
+
+    // Create a function composed of linear segments mapping data values to bucket indices.
+
+    __shared__ float segmentLowerBound[9];
+    __shared__ float segmentBaseIndex[9];
+    __shared__ float segmentIndexScale[9];
+    if (threadIdx.x == 0) {
+        segmentLowerBound[0] = elements[0]-0.2f*(elements[5]-elements[0]);
+        segmentLowerBound[1] = elements[5];
+        segmentLowerBound[2] = elements[10];
+        segmentLowerBound[3] = elements[20];
+        segmentLowerBound[4] = elements[30];
+        segmentLowerBound[5] = elements[40];
+        segmentLowerBound[6] = elements[50];
+        segmentLowerBound[7] = elements[60];
+        segmentLowerBound[8] = elements[63]+0.2f*(elements[63]-elements[58]);
+        segmentBaseIndex[0] = numBuckets/16;
+        segmentBaseIndex[1] = 3*numBuckets/16;
+        segmentBaseIndex[2] = 5*numBuckets/16;
+        segmentBaseIndex[3] = 7*numBuckets/16;
+        segmentBaseIndex[4] = 9*numBuckets/16;
+        segmentBaseIndex[5] = 11*numBuckets/16;
+        segmentBaseIndex[6] = 13*numBuckets/16;
+        segmentBaseIndex[7] = 15*numBuckets/16;
+        segmentBaseIndex[8] = numBuckets;
+        for (int i = 0; i < 8; i++)
+            if (segmentLowerBound[i+1] == segmentLowerBound[i])
+                segmentIndexScale[i] = 0;
+            else
+                segmentIndexScale[i] = (segmentBaseIndex[i+1]-segmentBaseIndex[i])/(segmentLowerBound[i+1]-segmentLowerBound[i]);
+    }
+    __syncthreads();
+
+    // Assign elements to buckets.
+
+    for (unsigned int index = blockDim.x*blockIdx.x+threadIdx.x; index < length; index += blockDim.x*gridDim.x) {
+        float key = (float) getValue(data[index]);
+        int segment;
+        for (segment = 0; segment < 7 && key > segmentLowerBound[segment+1]; segment++)
+            ;
+        unsigned int bucketIndex = segmentBaseIndex[segment]+(key-segmentLowerBound[segment])*segmentIndexScale[segment];
+        bucketIndex = min(max(0, bucketIndex), numBuckets-1);
+        offsetInBucket[index] = atomicAdd(&bucketOffset[bucketIndex], 1);
+        bucketOfElement[index] = bucketIndex;
+    }
+}
+
 /**
  * Sum the bucket sizes to compute the start position of each bucket.  This kernel
  * is executed as a single work group.

platforms/cuda/tests/TestCudaSort.cpp

@@ -6,7 +6,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2008-2016 Stanford University and the Authors.      *
+ * Portions copyright (c) 2008-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -59,7 +59,7 @@ class SortTrait : public CudaSort::SortTrait {
     const char* getSortKey() const {return "value";}
 };
 
-void verifySorting(vector<float> array) {
+void verifySorting(vector<float> array, bool uniform) {
     // Sort the array.
 
     System system;
@@ -72,7 +72,7 @@ void verifySorting(vector<float> array) {
     context.setAsCurrent();
     CudaArray data(context, array.size(), 4, "sortData");
     data.upload(array);
-    CudaSort sort(context, new SortTrait(), array.size());
+    CudaSort sort(context, new SortTrait(), array.size(), uniform);
     sort.sort(data);
     vector<float> sorted;
     data.download(sorted);
@@ -96,7 +96,8 @@ void testUniformValues() {
     vector<float> array(10000);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) genrand_real2(sfmt);
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 void testLogValues() {
@@ -106,7 +107,8 @@ void testLogValues() {
     vector<float> array(10000);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) log(genrand_real2(sfmt));
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 void testShortList() {
@@ -116,7 +118,8 @@ void testShortList() {
     vector<float> array(500);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) log(genrand_real2(sfmt));
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 int main(int argc, char* argv[]) {

platforms/opencl/include/OpenCLSort.h

@@ -9,7 +9,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2010-2018 Stanford University and the Authors.      *
+ * Portions copyright (c) 2010-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -77,8 +77,12 @@ public:
      *                   on the heap with the "new" operator.  This object takes over ownership of it,
      *                   and deletes it when the OpenCLSort is deleted.
      * @param length     the length of the arrays this object will be used to sort
+     * @param uniform    whether the input data is expected to follow a uniform or nonuniform
+     *                   distribution.  This argument is used only as a hint.  It allows parts
+     *                   of the algorithm to be tuned for faster performance on the expected
+     *                   distribution.
      */
-    OpenCLSort(OpenCLContext& context, SortTrait* trait, unsigned int length);
+    OpenCLSort(OpenCLContext& context, SortTrait* trait, unsigned int length, bool uniform=true);
     ~OpenCLSort();
     /**
      * Sort an array.
@@ -94,7 +98,7 @@ private:
     OpenCLArray buckets;
     cl::Kernel shortListKernel, shortList2Kernel, computeRangeKernel, assignElementsKernel, computeBucketPositionsKernel, copyToBucketsKernel, sortBucketsKernel;
     unsigned int dataLength, rangeKernelSize, positionsKernelSize, sortKernelSize;
-    bool isShortList, useShortList2;
+    bool isShortList, useShortList2, uniform;
 };
 
 /**

platforms/opencl/src/OpenCLNonbondedUtilities.cpp

@@ -305,7 +305,7 @@ void OpenCLNonbondedUtilities::initialize(const System& system) {
         sortedBlockBoundingBox.initialize(context, numAtomBlocks+1, 4*elementSize, "sortedBlockBoundingBox");
         oldPositions.initialize(context, numAtoms, 4*elementSize, "oldPositions");
         rebuildNeighborList.initialize<int>(context, 1, "rebuildNeighborList");
-        blockSorter = new OpenCLSort(context, new BlockSortTrait(context.getUseDoublePrecision()), numAtomBlocks);
+        blockSorter = new OpenCLSort(context, new BlockSortTrait(context.getUseDoublePrecision()), numAtomBlocks, false);
         vector<cl_uint> count(1, 0);
         interactionCount.upload(count);
         rebuildNeighborList.upload(count);

platforms/opencl/src/OpenCLSort.cpp

@@ -6,7 +6,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2010-2020 Stanford University and the Authors.      *
+ * Portions copyright (c) 2010-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -37,7 +37,8 @@
 using namespace OpenMM;
 using namespace std;
 
-OpenCLSort::OpenCLSort(OpenCLContext& context, SortTrait* trait, unsigned int length) : context(context), trait(trait), dataLength(length) {
+OpenCLSort::OpenCLSort(OpenCLContext& context, SortTrait* trait, unsigned int length, bool uniform) :
+        context(context), trait(trait), dataLength(length), uniform(uniform) {
     // Create kernels.
 
     std::map<std::string, std::string> replacements;
@@ -47,11 +48,13 @@ OpenCLSort::OpenCLSort(OpenCLContext& context, SortTrait* trait, unsigned int le
     replacements["MIN_KEY"] = trait->getMinKey();
     replacements["MAX_KEY"] = trait->getMaxKey();
     replacements["MAX_VALUE"] = trait->getMaxValue();
+    replacements["UNIFORM"] = (uniform ? "1" : "0");
     cl::Program program = context.createProgram(context.replaceStrings(OpenCLKernelSources::sort, replacements));
     shortListKernel = cl::Kernel(program, "sortShortList");
     shortList2Kernel = cl::Kernel(program, "sortShortList2");
     computeRangeKernel = cl::Kernel(program, "computeRange");
     assignElementsKernel = cl::Kernel(program, "assignElementsToBuckets");
+    assignElementsKernel = cl::Kernel(program, uniform ? "assignElementsToBuckets" : "assignElementsToBuckets2");
     computeBucketPositionsKernel = cl::Kernel(program, "computeBucketPositions");
     copyToBucketsKernel = cl::Kernel(program, "copyDataToBuckets");
     sortBucketsKernel = cl::Kernel(program, "sortBuckets");

platforms/opencl/src/kernels/sort.cl

@@ -77,6 +77,7 @@ __kernel void sortShortList2(__global const DATA_TYPE* restrict dataIn, __global
  */
 __kernel void computeRange(__global const DATA_TYPE* restrict data, uint length, __global KEY_TYPE* restrict range, __local KEY_TYPE* restrict minBuffer,
         __local KEY_TYPE* restrict maxBuffer, uint numBuckets, __global uint* restrict bucketOffset) {
+#if UNIFORM
     KEY_TYPE minimum = MAX_KEY;
     KEY_TYPE maximum = MIN_KEY;
 
@@ -106,7 +107,8 @@ __kernel void computeRange(__global const DATA_TYPE* restrict data, uint length,
         range[0] = minimum;
         range[1] = maximum;
     }
-    
+#endif
+
     // Clear the bucket counters in preparation for the next kernel.
 
     for (uint index = get_local_id(0); index < numBuckets; index += get_local_size(0))
@@ -114,7 +116,7 @@ __kernel void computeRange(__global const DATA_TYPE* restrict data, uint length,
 }
 
 /**
- * Assign elements to buckets.
+ * Assign elements to buckets.  This version is optimized for uniformly distributed data.
  */
 __kernel void assignElementsToBuckets(__global const DATA_TYPE* restrict data, uint length, uint numBuckets, __global const KEY_TYPE* restrict range,
         __global uint* restrict bucketOffset, __global uint* restrict bucketOfElement, __global uint* restrict offsetInBucket) {
@@ -137,6 +139,85 @@ __kernel void assignElementsToBuckets(__global const DATA_TYPE* restrict data, u
     }
 }
 
+/**
+ * Assign elements to buckets.  This version is optimized for non-uniformly distributed data.
+ */
+__kernel void assignElementsToBuckets2(__global const DATA_TYPE* restrict data, uint length, uint numBuckets, __global const KEY_TYPE* restrict range,
+        __global uint* restrict bucketOffset, __global uint* restrict bucketOfElement, __global uint* restrict offsetInBucket) {
+    // Load 64 datapoints and sort them to get an estimate of the data distribution.
+
+    __local KEY_TYPE elements[64];
+    if (get_local_id(0) < 64) {
+        int index = (int) (get_local_id(0)*length/64.0);
+        elements[get_local_id(0)] = getValue(data[index]);
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (unsigned int k = 2; k <= 64; k *= 2) {
+        for (unsigned int j = k/2; j > 0; j /= 2) {
+            if (get_local_id(0) < 64) {
+                int ixj = get_local_id(0)^j;
+                if (ixj > get_local_id(0)) {
+                    KEY_TYPE value1 = elements[get_local_id(0)];
+                    KEY_TYPE value2 = elements[ixj];
+                    bool ascending = (get_local_id(0)&k) == 0;
+                    KEY_TYPE lowKey = (ascending ? value1 : value2);
+                    KEY_TYPE highKey = (ascending ? value2 : value1);
+                    if (lowKey > highKey) {
+                        elements[get_local_id(0)] = value2;
+                        elements[ixj] = value1;
+                    }
+                }
+            }
+            barrier(CLK_LOCAL_MEM_FENCE);
+        }
+    }
+
+    // Create a function composed of linear segments mapping data values to bucket indices.
+
+    __local float segmentLowerBound[9];
+    __local float segmentBaseIndex[9];
+    __local float segmentIndexScale[9];
+    if (get_local_id(0) == 0) {
+        segmentLowerBound[0] = elements[0]-0.2f*(elements[5]-elements[0]);
+        segmentLowerBound[1] = elements[5];
+        segmentLowerBound[2] = elements[10];
+        segmentLowerBound[3] = elements[20];
+        segmentLowerBound[4] = elements[30];
+        segmentLowerBound[5] = elements[40];
+        segmentLowerBound[6] = elements[50];
+        segmentLowerBound[7] = elements[60];
+        segmentLowerBound[8] = elements[63]+0.2f*(elements[63]-elements[58]);
+        segmentBaseIndex[0] = numBuckets/16;
+        segmentBaseIndex[1] = 3*numBuckets/16;
+        segmentBaseIndex[2] = 5*numBuckets/16;
+        segmentBaseIndex[3] = 7*numBuckets/16;
+        segmentBaseIndex[4] = 9*numBuckets/16;
+        segmentBaseIndex[5] = 11*numBuckets/16;
+        segmentBaseIndex[6] = 13*numBuckets/16;
+        segmentBaseIndex[7] = 15*numBuckets/16;
+        segmentBaseIndex[8] = numBuckets;
+        for (int i = 0; i < 8; i++)
+            if (segmentLowerBound[i+1] == segmentLowerBound[i])
+                segmentIndexScale[i] = 0;
+            else
+                segmentIndexScale[i] = (segmentBaseIndex[i+1]-segmentBaseIndex[i])/(segmentLowerBound[i+1]-segmentLowerBound[i]);
+    }
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    // Assign elements to buckets.
+
+    for (unsigned int index = get_global_id(0); index < length; index += get_global_size(0)) {
+        float key = (float) getValue(data[index]);
+        int segment;
+        for (segment = 0; segment < 7 && key > segmentLowerBound[segment+1]; segment++)
+            ;
+        unsigned int bucketIndex = segmentBaseIndex[segment]+(key-segmentLowerBound[segment])*segmentIndexScale[segment];
+        bucketIndex = min(max((uint) 0, bucketIndex), numBuckets-1);
+        offsetInBucket[index] = atom_inc(&bucketOffset[bucketIndex]);
+        bucketOfElement[index] = bucketIndex;
+    }
+}
+
 /**
  * Sum the bucket sizes to compute the start position of each bucket.  This kernel
  * is executed as a single work group.

platforms/opencl/tests/TestOpenCLSort.cpp

@@ -6,7 +6,7 @@
  * Biological Structures at Stanford, funded under the NIH Roadmap for        *
  * Medical Research, grant U54 GM072970. See https://simtk.org.               *
  *                                                                            *
- * Portions copyright (c) 2008-2016 Stanford University and the Authors.      *
+ * Portions copyright (c) 2008-2021 Stanford University and the Authors.      *
  * Authors: Peter Eastman                                                     *
  * Contributors:                                                              *
  *                                                                            *
@@ -59,7 +59,7 @@ class SortTrait : public OpenCLSort::SortTrait {
     const char* getSortKey() const {return "value";}
 };
 
-void verifySorting(vector<float> array) {
+void verifySorting(vector<float> array, bool uniform) {
     // Sort the array.
 
     System system;
@@ -69,7 +69,7 @@ void verifySorting(vector<float> array) {
     context.initialize();
     OpenCLArray data(context, array.size(), sizeof(float), "sortData");
     data.upload(array);
-    OpenCLSort sort(context, new SortTrait(), array.size());
+    OpenCLSort sort(context, new SortTrait(), array.size(), uniform);
     sort.sort(data);
     vector<float> sorted;
     data.download(sorted);
@@ -93,7 +93,8 @@ void testUniformValues() {
     vector<float> array(10000);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) genrand_real2(sfmt);
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 void testLogValues() {
@@ -103,7 +104,8 @@ void testLogValues() {
     vector<float> array(10000);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) log(genrand_real2(sfmt));
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 void testShortList() {
@@ -113,7 +115,8 @@ void testShortList() {
     vector<float> array(500);
     for (int i = 0; i < (int) array.size(); i++)
         array[i] = (float) log(genrand_real2(sfmt));
-    verifySorting(array);
+    verifySorting(array, true);
+    verifySorting(array, false);
 }
 
 int main(int argc, char* argv[]) {