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Convert sum benchmark to use var<mat> #2

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Convert sum benchmark to use var<mat> #2

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1efaf1c
Convert sum benchmark to use `var<mat>`
bbbales2 Oct 23, 2020
c7b99a7
Converting more benchmarks to varmat
bbbales2 Jan 26, 2021
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4 changes: 2 additions & 2 deletions benchmark/stan/CMakeLists.txt
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Expand Up @@ -26,9 +26,9 @@ function(add_stan_executable name)
${PROJECT_SOURCE_DIR}/lib/stan-dev-math
${PROJECT_SOURCE_DIR}/lib/stan-dev-math/lib/tbb_2019_U8/include
${PROJECT_SOURCE_DIR}/lib/stan-dev-math/lib/boost_1.72.0
${PROJECT_SOURCE_DIR}/lib/stan-dev-math/lib/sundials_5.2.0/include)
${PROJECT_SOURCE_DIR}/lib/stan-dev-math/lib/sundials_5.6.1/include
${PROJECT_SOURCE_DIR}/lib/stan-dev-math/lib/eigen_3.3.9)
target_link_libraries(${exec}
Eigen3::Eigen
FastAD::FastAD
${TBB_LIB}
${TBBMALLOC_LIB}
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12 changes: 10 additions & 2 deletions benchmark/stan/driver.hpp
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Expand Up @@ -4,7 +4,7 @@

namespace adb {

template <class F>
template <class F, class V>
static void BM_stan(benchmark::State& state)
{
F f;
Expand All @@ -17,8 +17,16 @@ static void BM_stan(benchmark::State& state)

state.counters["N"] = x.size();

int i = 0;
for (auto _ : state) {
stan::math::gradient(f, x, fx, grad_fx);
V x_var(x);
stan::math::var fx_var = f(x_var);

fx_var.grad();
if(i == 0)
grad_fx = x_var.adj();
stan::math::recover_memory();
i++;
}

// sanity-check that output gradient is good
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17 changes: 11 additions & 6 deletions benchmark/stan/log_sum_exp.cpp
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Expand Up @@ -5,13 +5,18 @@ namespace adb {

struct LogSumExpFunc: LogSumExpFuncBase
{
stan::math::var operator()(const Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>& x) const
{
return stan::math::log_sum_exp(x);
}
template <typename T>
auto operator()(const T& x) const
{
return stan::math::log_sum_exp(x);
}
};

BENCHMARK_TEMPLATE(BM_stan, LogSumExpFunc)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, LogSumExpFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, LogSumExpFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
3 changes: 2 additions & 1 deletion benchmark/stan/matrix_product.cpp
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Expand Up @@ -15,7 +15,8 @@ struct MatrixProductFunc: MatrixProductFuncBase
}
};

BENCHMARK_TEMPLATE(BM_stan, MatrixProductFunc)
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, MatrixProductFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 16);

} // namespace adb
19 changes: 12 additions & 7 deletions benchmark/stan/normal_log_pdf.cpp
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Expand Up @@ -5,15 +5,20 @@ namespace adb {

struct NormalLogPdfFunc: NormalLogPdfFuncBase
{
auto operator()(const Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>& x) const
{
stan::math::var mu = mu_;
stan::math::var sigma = sigma_;
return stan::math::normal_lpdf(x, mu, sigma);
}
template <typename T>
auto operator()(const T& x) const
{
stan::math::var mu = mu_;
stan::math::var sigma = sigma_;
return stan::math::normal_lpdf(x, mu, sigma);
}
};

BENCHMARK_TEMPLATE(BM_stan, NormalLogPdfFunc)
using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, NormalLogPdfFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, NormalLogPdfFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
3 changes: 2 additions & 1 deletion benchmark/stan/prod.cpp
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Expand Up @@ -6,7 +6,8 @@ namespace adb {
struct ProdFunc: ProdFuncBase
{};

BENCHMARK_TEMPLATE(BM_stan, ProdFunc)
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, ProdFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
22 changes: 19 additions & 3 deletions benchmark/stan/prod_iter.cpp
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Expand Up @@ -4,9 +4,25 @@
namespace adb {

struct ProdIterFunc: ProdIterFuncBase
{};
{
template <class T>
stan::math::var operator()(const T& x) const {
using namespace stan::math;

BENCHMARK_TEMPLATE(BM_stan, ProdIterFunc)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
stan::math::var res = 1.0;
for(size_t i = 0; i < x.size(); i++) {
res *= x.coeffRef(i);
}

return res;
}
};

using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, ProdIterFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, ProdIterFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
32 changes: 18 additions & 14 deletions benchmark/stan/regression.cpp
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Expand Up @@ -5,22 +5,26 @@ namespace adb {

struct RegressionFunc: RegressionFuncBase
{
auto operator()(const Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>& x) const
{
using namespace stan::math;
using vec_t = Eigen::Matrix<var, Eigen::Dynamic, 1>;
size_t N = (x.size() - 2);
Eigen::Map<const vec_t> w(x.data(), N);
auto& b = x(N);
auto& sigma = x(N + 1);
return normal_lpdf(y, multiply(X, w) + b * vec_t::Ones(1000), sigma) +
normal_lpdf(w, 0., 1.) +
normal_lpdf(b, 0., 1.) -
uniform_lpdf(sigma, 0.1, 10.);
}
template <typename T>
auto operator()(const T& x) const
{
using namespace stan::math;
size_t N = (x.size() - 2);
const auto& w = x.head(N);
const auto& b = x(N);
const auto& sigma = x(N + 1);
return normal_lpdf(y, add(multiply(X, w), b), sigma) +
normal_lpdf(w, 0., 1.) +
normal_lpdf(b, 0., 1.) -
uniform_lpdf(sigma, 0.1, 10.);
}
};

BENCHMARK_TEMPLATE(BM_stan, RegressionFunc)
using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, RegressionFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, RegressionFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
3 changes: 2 additions & 1 deletion benchmark/stan/stochastic_volatility.cpp
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Expand Up @@ -64,7 +64,8 @@ struct StochasticVolatilityFunc: StochasticVolatilityFuncBase
}
};

BENCHMARK_TEMPLATE(BM_stan, StochasticVolatilityFunc)
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, StochasticVolatilityFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
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15 changes: 10 additions & 5 deletions benchmark/stan/sum.cpp
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Expand Up @@ -5,13 +5,18 @@ namespace adb {

struct SumFunc: SumFuncBase
{
stan::math::var operator()(const Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>& x) const
{
return stan::math::sum(x);
}
template <typename T>
stan::math::var operator()(const T& x) const
{
return stan::math::sum(x);
}
};

BENCHMARK_TEMPLATE(BM_stan, SumFunc)
using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, SumFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, SumFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
20 changes: 18 additions & 2 deletions benchmark/stan/sum_iter.cpp
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Expand Up @@ -4,9 +4,25 @@
namespace adb {

struct SumIterFunc: SumIterFuncBase
{};
{
template <class T>
stan::math::var operator()(const T& x) const {
using namespace stan::math;

BENCHMARK_TEMPLATE(BM_stan, SumIterFunc)
stan::math::var res = 0.0;
for(size_t i = 0; i < x.size(); i++) {
res += x.coeffRef(i);
}

return res;
}
};

using varmat = stan::math::var_value<Eigen::VectorXd>;
using matvar = Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>;
BENCHMARK_TEMPLATE(BM_stan, SumIterFunc, matvar)
-> RangeMultiplier(2) -> Range(1, 1 << 14);
BENCHMARK_TEMPLATE(BM_stan, SumIterFunc, varmat)
-> RangeMultiplier(2) -> Range(1, 1 << 14);

} // namespace adb
2 changes: 1 addition & 1 deletion setup.sh
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Expand Up @@ -96,7 +96,7 @@ fi

# setup STAN
if [ ! -d "$stan" ]; then
git clone --depth 1 --branch v3.3.0 https://github.com/stan-dev/math.git $stan
git clone --depth 1 --branch v4.0.0 https://github.com/stan-dev/math.git $stan
cd $stan
echo "CXX=g++-10" > make/local
make -j4 -f make/standalone math-libs
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