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Remove array_ref from benchmarks
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@PetroZarytskyi @vgvassilev
PetroZarytskyi authored and vgvassilev committed Mar 21, 2024
1 parent 761dbfc commit d908e8e
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Showing 7 changed files with 20 additions and 44 deletions.
5 changes: 2 additions & 3 deletions benchmark/AlgorithmicComplexity.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -63,11 +63,10 @@ static void BM_ReverseGausP(benchmark::State& state) {
long double sum = 0;
int dim = 5;
double result[5] = {};
clad::array_ref<double> result_ref(result, dim);
for (auto _ : state) {
dfdp_grad.execute(x, p, /*sigma*/ 2, dim, result_ref);
dfdp_grad.execute(x, p, /*sigma*/ 2, dim, result);
for (int i = 0; i < dim; i++) {
benchmark::DoNotOptimize(sum += result_ref[i]);
benchmark::DoNotOptimize(sum += result[i]);
result[i] = 0; // clear for the next benchmark iteration
}
}
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21 changes: 6 additions & 15 deletions benchmark/EnzymeCladComparison.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -36,9 +36,8 @@ static void BM_VectorForwardModeAddArrayAndMultiplyWithScalarsExecute(
int dn = 0;
double arr[5] = {1, 2, 3, 4, 5};
double darr[5] = {0};
clad::array_ref<double> darr_ref(darr, n);
for (auto _ : state) {
grad.execute(arr, x, y, 5, darr_ref, &dx, &dy, &dn);
grad.execute(arr, x, y, 5, darr, &dx, &dy, &dn);
dx = 0;
dy = 0;
for (int i = 0; i < n; i++)
Expand Down Expand Up @@ -87,9 +86,8 @@ static void BM_VectorForwardModeSumExecute(benchmark::State& state) {
auto grad = clad::differentiate<clad::opts::vector_mode>(sum, "p");
double inputs[] = {1, 2, 3, 4, 5};
double result[5] = {};
clad::array_ref<double> result_ref(result, 5);
for (auto _ : state) {
grad.execute(inputs, /*dim*/ 5, result_ref);
grad.execute(inputs, /*dim*/ 5, result);
for (int i = 0; i < 5; i++)
result[i] = 0;
}
Expand Down Expand Up @@ -126,9 +124,8 @@ static void BM_VectorForwardModeProductExecute(benchmark::State& state) {
auto grad = clad::differentiate<clad::opts::vector_mode>(product, "p");
double inputs[] = {1, 2, 3, 4, 5};
double result[5] = {};
clad::array_ref<double> result_ref(result, 5);
for (auto _ : state) {
grad.execute(inputs, /*dim*/ 5, result_ref);
grad.execute(inputs, /*dim*/ 5, result);
for (int i = 0; i < 5; i++)
result[i] = 0;
}
Expand Down Expand Up @@ -210,12 +207,10 @@ static void BM_ReverseModeWeightedSum(benchmark::State& state) {

double dinp[n];
double dweights[n];
clad::array_ref<double> dinp_ref(dinp, n);
clad::array_ref<double> dweights_ref(dweights, n);

double sum = 0;
for (auto _ : state) {
grad.execute(inputs, weights, n, dinp_ref, dweights_ref);
grad.execute(inputs, weights, n, dinp, dweights);
for (int i = 0; i < n; ++i) {
sum += dinp[i] + dweights[i];
dinp[i] = 0;
Expand All @@ -241,12 +236,10 @@ static void BM_VectorForwardModeWeightedSum(benchmark::State& state) {

double dinp[n];
double dweights[n];
clad::array_ref<double> dinp_ref(dinp, n);
clad::array_ref<double> dweights_ref(dweights, n);

double sum = 0;
for (auto _ : state) {
vm_grad.execute(inputs, weights, n, dinp_ref, dweights_ref);
vm_grad.execute(inputs, weights, n, dinp, dweights);
for (int i = 0; i < n; ++i) {
sum += dinp[i] + dweights[i];
dinp[i] = 0;
Expand All @@ -271,12 +264,10 @@ static void BM_ReverseModeWeightedSumEnzyme(benchmark::State& state) {

double dinp[n];
double dweights[n];
clad::array_ref<double> dinp_ref(dinp, n);
clad::array_ref<double> dweights_ref(dweights, n);

double sum = 0;
for (auto _ : state) {
grad.execute(inputs, weights, n, dinp_ref, dweights_ref);
grad.execute(inputs, weights, n, dinp, dweights);
for (int i = 0; i < n; ++i) {
sum += dinp[i] + dweights[i];
dinp[i] = 0;
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3 changes: 1 addition & 2 deletions benchmark/MemoryComplexity.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -89,10 +89,9 @@ static void BM_ReverseGausMemoryP(benchmark::State& state) {
x[i] = 1;
p[i] = i;
}
clad::array_ref<double> result_ref(result, dim);
AddBMCounterRAII MemCounters(*mm.get(), state);
for (auto _ : state) {
dfdp_grad.execute(x, p, /*sigma*/ 2, dim, result_ref);
dfdp_grad.execute(x, p, /*sigma*/ 2, dim, result);
}
}
BENCHMARK(BM_ReverseGausMemoryP)
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8 changes: 3 additions & 5 deletions benchmark/Simple.cpp
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Expand Up @@ -27,7 +27,7 @@ static void BM_ForwardModePow2FwdDecl(benchmark::State &state) {
BENCHMARK(BM_ForwardModePow2FwdDecl);

// Benchmark calling the gradient via CladFunction::execute.
inline void sum_grad_0(double*, int, clad::array_ref<double>);
inline void sum_grad_0(double*, int, double*);
static void BM_ReverseModeSumFwdDecl(benchmark::State &state) {
auto grad = clad::gradient(sum, "p");
(void) grad;
Expand Down Expand Up @@ -63,10 +63,9 @@ static void BM_VectorForwardModeSumFwdDecl(benchmark::State &state) {
(void) vm_grad;
double inputs[] = {1, 2, 3, 4, 5};
double result[3] = {};
clad::array_ref<double> result_ref(result, 3);
unsigned long long sum = 0;
for (auto _ : state) {
sum_dvec_0(inputs,/*dim*/ 3, result_ref);
sum_dvec_0(inputs, /*dim*/ 3, result);
benchmark::DoNotOptimize(sum += result[0] + result[1] + result[2]);
}
}
Expand All @@ -78,10 +77,9 @@ static void BM_VectorForwardModeSumExecute(benchmark::State &state) {
auto vm_grad = clad::differentiate<clad::opts::vector_mode>(sum, "p");
double inputs[] = {1, 2, 3, 4, 5};
double result[3] = {};
clad::array_ref<double> result_ref(result, 3);
unsigned long long sum = 0;
for (auto _ : state) {
vm_grad.execute(inputs,/*dim*/ 3, result_ref);
vm_grad.execute(inputs, /*dim*/ 3, result);
benchmark::DoNotOptimize(sum += result[0] + result[1] + result[2]);
}
}
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4 changes: 1 addition & 3 deletions benchmark/VectorModeComparison.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -53,12 +53,10 @@ static void BM_ReverseModeWeightedSum(benchmark::State& state) {

double dinp[n];
double dweights[n];
clad::array_ref<double> dinp_ref(dinp, n);
clad::array_ref<double> dweights_ref(dweights, n);

double sum = 0;
for (auto _ : state) {
grad.execute(inputs, weights, n, dinp_ref, dweights_ref);
grad.execute(inputs, weights, n, dinp, dweights);
for (int i = 0; i < n; ++i) {
sum += dinp[i] + dweights[i];
dinp[i] = 0;
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19 changes: 5 additions & 14 deletions demos/Arrays.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -52,20 +52,14 @@ int main() {

double darr[3] = {0, 0, 0};
double dweights[3] = {0, 0, 0};
// clad::array_ref is used by clad::gradient to keep track of the array size
// being sent into the generated gradient. Since clad::array_ref is a wrapper
// for the supplied array any changes to it will be reflected in the array and
// vice versa
clad::array_ref<double> darr_ref(darr, 3);
clad::array_ref<double> dweights_ref(dweights, 3);

weighted_avg_dall.execute(arr, weights, darr_ref, dweights_ref);

weighted_avg_dall.execute(arr, weights, darr, dweights);
printf("Reverse Mode w.r.t. all:\n darr = {%.2g, %.2g, %.2g}\n dweights = "
"{%.2g, %.2g, %.2g}\n",
darr[0], darr[1], darr[2], dweights[0], dweights[1], dweights[2]);

darr[0] = darr[1] = darr[2] = 0;
weighted_avg_darr.execute(arr, weights, darr_ref);
weighted_avg_darr.execute(arr, weights, darr);
printf("Reverse Mode w.r.t. arr:\n darr = {%.2g, %.2g, %.2g}\n", darr[0],
darr[1], darr[2]);

Expand All @@ -81,10 +75,7 @@ int main() {
double matrix_all[36] = {0};
// double matrix_arr[9] = {0};

clad::array_ref<double> matrix_all_ref(matrix_all, 36);
// clad::array_ref<double> matrix_arr_ref(matrix_arr, 9);

hessian_all.execute(arr, weights, matrix_all_ref);
hessian_all.execute(arr, weights, matrix_all);
printf("Hessian Mode w.r.t. to all:\n matrix =\n"
" {%.2g, %.2g, %.2g, %.2g, %.2g, %.2g}\n"
" {%.2g, %.2g, %.2g, %.2g, %.2g, %.2g}\n"
Expand All @@ -102,7 +93,7 @@ int main() {
matrix_all[28], matrix_all[29], matrix_all[30], matrix_all[31],
matrix_all[32], matrix_all[33], matrix_all[34], matrix_all[35]);

/*hessian_arr.execute(arr, weights, matrix_arr_ref);
/*hessian_arr.execute(arr, weights, matrix_arr);
printf("Hessian Mode w.r.t. to arr:\n matrix =\n"
" {%.2g, %.2g, %.2g}\n"
" {%.2g, %.2g, %.2g}\n"
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4 changes: 2 additions & 2 deletions demos/Jupyter/Intro.ipynb
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Expand Up @@ -143,7 +143,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"The code is: void fn_grad(double x, double y, clad::array_ref<double> _d_x, clad::array_ref<double> _d_y) {\n",
"The code is: void fn_grad(double x, double y, double *_d_x, double *_d_y) {\n",
" double _t2;\n",
" double _t3;\n",
" double _t4;\n",
Expand Down Expand Up @@ -356,7 +356,7 @@
"output_type": "stream",
"text": [
"The code is: \n",
"void fn_grad(double x, double y, clad::array_ref<double> _d_x, clad::array_ref<double> _d_y, double &_final_error) {\n",
"void fn_grad(double x, double y, double *_d_x, double *_d_y, double &_final_error) {\n",
" double _t2;\n",
" double _t3;\n",
" double _t4;\n",
Expand Down

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