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icicle/examples/c++/multiply/example.cu
2024-01-31 08:59:21 +02:00

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#include <iostream>
#include <iomanip>
#include <chrono>
#include <nvml.h>
#define CURVE_ID 1
#include "curves/curve_config.cuh"
#include "utils/device_context.cuh"
#include "utils/vec_ops.cu"
using namespace curve_config;
// select scalar or point field
//typedef scalar_t T;
typedef point_field_t T;
int vector_mult(T* vec_b, T* vec_a, T* vec_result, size_t n_elments, device_context::DeviceContext ctx)
{
const bool is_on_device = true;
const bool is_montgomery = false;
cudaError_t err = vec_ops::Mul<T,T>(vec_a, vec_b, n_elments, is_on_device, is_montgomery, ctx, vec_result);
if (err != cudaSuccess) {
std::cerr << "Failed to multiply vectors - " << cudaGetErrorString(err) << std::endl;
return 0;
}
return 0;
}
int main(int argc, char** argv)
{
const unsigned vector_size = 1 << 15;
const unsigned repetitions = 1 << 15;
cudaError_t err;
nvmlInit();
nvmlDevice_t device;
nvmlDeviceGetHandleByIndex(0, &device); // for GPU 0
std::cout << "Icicle-Examples: vector multiplications" << std::endl;
char name[NVML_DEVICE_NAME_BUFFER_SIZE];
if (nvmlDeviceGetName(device, name, NVML_DEVICE_NAME_BUFFER_SIZE) == NVML_SUCCESS) {
std::cout << "GPU Model: " << name << std::endl;
} else {
std::cerr << "Failed to get GPU model name." << std::endl;
}
unsigned power_limit;
nvmlDeviceGetPowerManagementLimit(device, &power_limit);
std::cout << "Vector size: " << vector_size << std::endl;
std::cout << "Repetitions: " << repetitions << std::endl;
std::cout << "Power limit: " << std::fixed << std::setprecision(3) << 1.0e-3 * power_limit << " W" << std::endl;
unsigned int baseline_power;
nvmlDeviceGetPowerUsage(device, &baseline_power);
std::cout << "Baseline power: " << std::fixed << std::setprecision(3) << 1.0e-3 * baseline_power << " W" << std::endl;
unsigned baseline_temperature;
if (nvmlDeviceGetTemperature(device, NVML_TEMPERATURE_GPU, &baseline_temperature) == NVML_SUCCESS) {
std::cout << "Baseline GPU Temperature: " << baseline_temperature << " C" << std::endl;
} else {
std::cerr << "Failed to get GPU temperature." << std::endl;
}
// host data
T* host_in1 = (T*)malloc(vector_size * sizeof(T));
T* host_in2 = (T*)malloc(vector_size * sizeof(T));
std::cout << "Initializing vectors with random data" << std::endl;
T::RandHostMany(host_in1, vector_size);
T::RandHostMany(host_in2, vector_size);
// device data
device_context::DeviceContext ctx = device_context::get_default_device_context();
T* device_in1;
T* device_in2;
T* device_out;
err = cudaMalloc((void**)&device_in1, vector_size * sizeof(T));
if (err != cudaSuccess) {
std::cerr << "Failed to allocate device memory - " << cudaGetErrorString(err) << std::endl;
return 0;
}
err = cudaMalloc((void**)&device_in2, vector_size * sizeof(T));
if (err != cudaSuccess) {
std::cerr << "Failed to allocate device memory - " << cudaGetErrorString(err) << std::endl;
return 0;
}
err = cudaMalloc((void**)&device_out, vector_size * sizeof(T));
if (err != cudaSuccess) {
std::cerr << "Failed to allocate device memory - " << cudaGetErrorString(err) << std::endl;
return 0;
}
// copy from host to device
err = cudaMemcpy(device_in1, host_in1, vector_size * sizeof(T), cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
std::cerr << "Failed to copy data from host to device - " << cudaGetErrorString(err) << std::endl;
return 0;
}
err = cudaMemcpy(device_in2, host_in2, vector_size * sizeof(T), cudaMemcpyHostToDevice);
if (err != cudaSuccess) {
std::cerr << "Failed to copy data from host to device - " << cudaGetErrorString(err) << std::endl;
return 0;
}
std::cout << "Starting warm-up" << std::endl;
// Warm-up loop
for (int i = 0; i < repetitions; i++) {
vector_mult(device_in1, device_in2, device_out, vector_size, ctx);
}
std::cout << "Starting benchmarking" << std::endl;
unsigned power_before;
nvmlDeviceGetPowerUsage(device, &power_before);
std::cout << "Power before: " << std::fixed << std::setprecision(3) << 1.0e-3 * power_before << " W" << std::endl;
std::cout << "Power utilization: " << std::fixed << std::setprecision(1) << (float)100.0 * power_before / power_limit
<< " %" << std::endl;
unsigned temperature_before;
if (nvmlDeviceGetTemperature(device, NVML_TEMPERATURE_GPU, &temperature_before) == NVML_SUCCESS) {
std::cout << "GPU Temperature before: " << temperature_before << " C" << std::endl;
} else {
std::cerr << "Failed to get GPU temperature." << std::endl;
}
auto start_time = std::chrono::high_resolution_clock::now();
// Benchmark loop
for (int i = 0; i < repetitions; i++) {
vector_mult(device_in1, device_in2, device_out, vector_size, ctx);
}
auto end_time = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time);
std::cout << "Elapsed time: " << duration.count() << " microseconds" << std::endl;
unsigned power_after;
nvmlDeviceGetPowerUsage(device, &power_after);
std::cout << "Power after: " << std::fixed << std::setprecision(3) << 1.0e-3 * power_after << " W" << std::endl;
std::cout << "Power utilization: " << std::fixed << std::setprecision(1) << (float)100.0 * power_after / power_limit
<< " %" << std::endl;
unsigned temperature_after;
if (nvmlDeviceGetTemperature(device, NVML_TEMPERATURE_GPU, &temperature_after) == NVML_SUCCESS) {
std::cout << "GPU Temperature after: " << temperature_after << " C" << std::endl;
} else {
std::cerr << "Failed to get GPU temperature." << std::endl;
}
// Report performance in GMPS: Giga Multiplications Per Second
double GMPS = 1.0e-9 * repetitions * vector_size / (1.0e-6 * duration.count());
std::cout << "Performance: " << GMPS << " Giga Multiplications Per Second" << std::endl;
// Optional: validate multiplication
T* host_out = (T*)malloc(vector_size * sizeof(T));
cudaMemcpy(host_out, device_out, vector_size * sizeof(T), cudaMemcpyDeviceToHost);
// validate multiplication here...
// clean up and exit
free(host_in1);
free(host_in2);
free(host_out);
cudaFree(device_in1);
cudaFree(device_in2);
cudaFree(device_out);
nvmlShutdown();
return 0;
}