rocm-systems/catch/unit/module/hipModuleLoadDataMultThreadOnMultGPU.cc

/*
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OUT OF OR INN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*/

/*
This testcase verifies the multithreaded scenario of
hipModuleLoadData API on MultiGPU system
*/

#include <fstream>
#include <vector>

#include "hip_test_common.hh"
#include "hip_test_checkers.hh"

#define LEN 64
#define SIZE LEN << 2
#define THREADS 8

#define FILENAME "module_kernels.code"
#define kernel_name "hello_world"

/*
This function reads the kernel code object file into buffer
*/
static std::vector<char> load_file() {
  std::ifstream file(FILENAME, std::ios::binary | std::ios::ate);
  std::streamsize fsize = file.tellg();
  file.seekg(0, std::ios::beg);

  std::vector<char> buffer(fsize);
  if (!file.read(buffer.data(), fsize)) {
    INFO("could not open code object " << FILENAME);
    REQUIRE(false);
  }
  return buffer;
}

/*
Thread function
1. Loads the module using hipModuleLoadData API
2. Initializes 2 device variables.
3. Launches kernel which copies one data into another.
4. validates the result and returns it to the caller using
   std::ref variable.
*/
static void run(const std::vector<char>& buffer, int deviceNo,
                bool &testResult) {
  hipSetDevice(deviceNo);
  hipModule_t Module;
  hipFunction_t Function;
  float *A{nullptr}, *B{nullptr}, *Ad{nullptr}, *Bd{nullptr};
  testResult = true;
  HipTest::initArrays<float>(&Ad, &Bd, nullptr,
                             &A, &B, nullptr,
                             LEN, false);
  HIPCHECK(hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice));
  HIPCHECK(hipMemcpy(Bd, B, SIZE, hipMemcpyHostToDevice));

  HIPCHECK(hipModuleLoadData(&Module, &buffer[0]));
  HIPCHECK(hipModuleGetFunction(&Function, Module, kernel_name));

  hipStream_t stream;
  HIPCHECK(hipStreamCreate(&stream));

  struct {
    void* _Ad;
    void* _Bd;
  } args;
  args._Ad = static_cast<void*>(Ad);
  args._Bd = static_cast<void*>(Bd);
  size_t size = sizeof(args);

  void* config[] = {HIP_LAUNCH_PARAM_BUFFER_POINTER, &args,
                    HIP_LAUNCH_PARAM_BUFFER_SIZE, &size,
                    HIP_LAUNCH_PARAM_END};
  HIPCHECK(hipModuleLaunchKernel(Function, 1, 1, 1, LEN,
                                 1, 1, 0, stream, NULL,
                                 reinterpret_cast<void**>(&config)));

  HIPCHECK(hipStreamSynchronize(stream));

  HIPCHECK(hipStreamDestroy(stream));

  HIPCHECK(hipModuleUnload(Module));

  HIPCHECK(hipMemcpy(B, Bd, SIZE, hipMemcpyDeviceToHost));

  for (uint32_t i = 0; i < LEN; i++) {
     REQUIRE(A[i] == B[i]);
  }
  HipTest::freeArrays<float>(Ad, Bd, nullptr,
                             A, B, nullptr,
                             false);
}

/*
Thread class inherited from std::thread
*/
struct joinable_thread : std::thread {
  template <class... Xs>
  joinable_thread(Xs&&... xs) : std::thread(std::forward<Xs>(xs)...) {} // NOLINT

  joinable_thread& operator=(joinable_thread&& other) = default;
  joinable_thread(joinable_thread&& other)      = default;

  ~joinable_thread() {
    if (this->joinable())
      this->join();
  }
};

/*
This API is triggered form the test case where in
1. Creates the thread object.
2. Loops through the number of GPUs and launches multiple threads.
*/
static void run_multi_threads(uint32_t n, const std::vector<char>& buffer) {
  int numDevices = 0;
  HIPCHECK(hipGetDeviceCount(&numDevices));
  bool testResult = false;
  std::vector<joinable_thread> threads;

  for (int deviceNo=0; deviceNo < numDevices; ++deviceNo) {
    for (uint32_t i = 0; i < n; i++) {
    threads.emplace_back(std::thread{[&, buffer] {
    run(buffer, deviceNo, std::ref(testResult));
    }});
    }
  }
}
/*
The testcase verifies the multithreaded funtionality on MGPU system
1. Loads the kernel file by calling load_file API
2. Gets the host thread count
3. Creates multiple threads in parallel where in each thread initializes
   2 device variables and loads the kernel using hipModuleLoadData API.
   The kernel copies the data from one variable to another.Then the thread
   validates both the variables.
*/
TEST_CASE("Unit_hipModuleLoadData_MGpuMultiThread") {
  auto buffer = load_file();
  auto file_size = buffer.size() / (1024 * 1024);
  auto thread_count =  HipTest::getHostThreadCount(file_size + 10);
  run_multi_threads(thread_count, buffer);
}