rocm-systems/tests/src/printf/hipPrintfBasic.cpp

/*
Copyright (c) 2020 - present Advanced Micro Devices, Inc. All rights reserved.

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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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*/

/* HIT_START
 * BUILD: %t %s EXCLUDE_HIP_PLATFORM nvidia
 * TEST: %t EXCLUDE_HIP_PLATFORM nvidia
 * HIT_END
 */

#include "test_common.h"
#include "printf_common.h"
#include <vector>

// Global string constants don't work inside device functions, so we
// use a macro to repeat the declaration in host and device contexts.
DECLARE_DATA();

__global__ void kernel_uniform0(int *retval) {
  uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  retval[tid] = printf("Hello World\n");
}

static void test_uniform0(int *retval, uint num_blocks,
                          uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;
  for (uint i = 0; i != num_threads; ++i) {
    retval[i] = 0x23232323;
  }

  hipLaunchKernelGGL(kernel_uniform0, dim3(num_blocks), dim3(threads_per_block),
                     0, 0, retval);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  for (uint ii = 0; ii != num_threads; ++ii) {
    HIPASSERT(retval[ii] == strlen("Hello World\n"));
  }

  std::map<std::string, int> linecount;
  for (std::string line; std::getline(CapturedData, line);) {
    linecount[line]++;
  }

  HIPASSERT(linecount.size() == 1);
  HIPASSERT(linecount["Hello World"] == num_threads);
}

__global__ void kernel_uniform1(int *retval) {
  uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  retval[tid] = printf("Six times Eight is %d\n", 42);
}

static void test_uniform1(int *retval, uint num_blocks,
                          uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;
  for (uint i = 0; i != num_threads; ++i) {
    retval[i] = 0x23232323;
  }

  hipLaunchKernelGGL(kernel_uniform1, dim3(num_blocks), dim3(threads_per_block),
                     0, 0, retval);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  for (uint ii = 0; ii != num_threads; ++ii) {
    HIPASSERT(retval[ii] == strlen("Six times Eight is 42") + 1);
  }

  std::map<std::string, int> linecount;
  for (std::string line; std::getline(CapturedData, line);) {
    linecount[line]++;
  }

  HIPASSERT(linecount.size() == 1);
  HIPASSERT(linecount["Six times Eight is 42"] == num_threads);
}

__global__ void kernel_divergent0(int *retval) {
  uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  retval[tid] = printf("Thread ID: %d\n", tid);
}

static void test_divergent0(int *retval, uint num_blocks,
                            uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;
  for (uint i = 0; i != num_threads; ++i) {
    retval[i] = 0x23232323;
  }

  hipLaunchKernelGGL(kernel_divergent0, dim3(num_blocks),
                     dim3(threads_per_block), 0, 0, retval);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  for (uint ii = 0; ii != 10; ++ii) {
    HIPASSERT(retval[ii] == 13);
  }

  for (uint ii = 10; ii != num_threads; ++ii) {
    HIPASSERT(retval[ii] == 14);
  }

  std::vector<uint> threadIds;
  for (std::string line; std::getline(CapturedData, line);) {
    auto pos = line.find(':');
    HIPASSERT(line.substr(0, pos) == "Thread ID");
    threadIds.push_back(std::stoul(line.substr(pos + 2)));
  }

  std::sort(threadIds.begin(), threadIds.end());
  HIPASSERT(threadIds.size() == num_threads);
  HIPASSERT(threadIds.back() == num_threads - 1);
}

__global__ void kernel_divergent1(int *retval) {
  uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  if (tid % 2) {
    retval[tid] = printf("Hello World\n");
  } else {
    retval[tid] = -1;
  }
}

static void test_divergent1(int *retval, uint num_blocks,
                            uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;
  for (uint i = 0; i != num_threads; ++i) {
    retval[i] = 0x23232323;
  }

  hipLaunchKernelGGL(kernel_divergent1, dim3(num_blocks),
                     dim3(threads_per_block), 0, 0, retval);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  for (uint ii = 0; ii != num_threads; ++ii) {
    if (ii % 2) {
      HIPASSERT(retval[ii] == strlen("Hello World\n"));
    } else {
      HIPASSERT(retval[ii] == -1);
    }
  }

  std::map<std::string, int> linecount;
  for (std::string line; std::getline(CapturedData, line);) {
    linecount[line]++;
  }

  HIPASSERT(linecount.size() == 1);
  HIPASSERT(linecount["Hello World"] == num_threads / 2);
}

__global__ void kernel_series(int *retval) {
  DECLARE_DATA();

  const uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  int result = 0;

  result += printf("%s\n", msg_long1);
  result += printf("%s\n", msg_short);
  result += printf("%s\n", msg_long2);

  retval[tid] = result;
}

static void test_series(int *retval, uint num_blocks, uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;
  for (uint i = 0; i != num_threads; ++i) {
    retval[i] = 0x23232323;
  }

  hipLaunchKernelGGL(kernel_series, dim3(num_blocks), dim3(threads_per_block),
                     0, 0, retval);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  for (uint ii = 0; ii != num_threads; ++ii) {
    HIPASSERT(retval[ii] ==
              strlen(msg_long1) + strlen(msg_short) + strlen(msg_long2) + 3);
  }

  std::map<std::string, int> linecount;
  for (std::string line; std::getline(CapturedData, line);) {
    linecount[line]++;
  }

  HIPASSERT(linecount.size() == 3);
  HIPASSERT(linecount[msg_long1] == num_threads);
  HIPASSERT(linecount[msg_long2] == num_threads);
  HIPASSERT(linecount[msg_short] == num_threads);
}

__global__ void kernel_divergent_loop() {
  DECLARE_DATA();

  const uint tid = hipThreadIdx_x + hipBlockIdx_x * hipBlockDim_x;
  int result = 0;

  for (int i = 0; i <= tid; ++i) {
    printf("%d\n", i);
  }
}

static void test_divergent_loop(uint num_blocks, uint threads_per_block) {
  CaptureStream captured(stdout);

  uint num_threads = num_blocks * threads_per_block;

  hipLaunchKernelGGL(kernel_divergent_loop, dim3(num_blocks), dim3(threads_per_block),
                     0, 0);
  hipStreamSynchronize(0);
  auto CapturedData = captured.getCapturedData();

  std::map<int, int> count;
  while (true) {
    int i;
    CapturedData >> i;
    if (CapturedData.fail())
      break;
    count[i]++;
  }

  HIPASSERT(count.size() == num_threads);
  for (int i = 0; i != num_threads; ++i) {
    HIPASSERT(count[i] == num_threads - i);
  }
}

int main() {
  uint num_blocks = 1;
  uint threads_per_block = 64;
  uint num_threads = num_blocks * threads_per_block;

  void *retval_void;
  HIPCHECK(hipHostMalloc(&retval_void, 4 * num_threads));
  auto retval = reinterpret_cast<int *>(retval_void);

  test_uniform0(retval, num_blocks, threads_per_block);
  test_uniform1(retval, num_blocks, threads_per_block);
  test_divergent0(retval, num_blocks, threads_per_block);
  test_divergent1(retval, num_blocks, threads_per_block);
  test_series(retval, num_blocks, threads_per_block);
  test_divergent_loop(num_blocks, threads_per_block);

  passed();
}