mlu_info.cc 13.8 KB
Newer Older
F
fwenguang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/fluid/platform/device/mlu/mlu_info.h"
16

F
fwenguang 已提交
17 18
#include <mutex>
#include <vector>
19

F
fwenguang 已提交
20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118
#include "gflags/gflags.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/platform/device/mlu/enforce.h"
#include "paddle/fluid/platform/lock_guard_ptr.h"
#include "paddle/fluid/platform/monitor.h"
#include "paddle/fluid/string/split.h"

DECLARE_double(fraction_of_gpu_memory_to_use);
DECLARE_uint64(initial_gpu_memory_in_mb);
DECLARE_uint64(reallocate_gpu_memory_in_mb);
DECLARE_uint64(gpu_memory_limit_mb);

constexpr static float fraction_reserve_mlu_memory = 0.05f;

PADDLE_DEFINE_EXPORTED_string(
    selected_mlus, "",
    "A list of device ids separated by comma, like: 0,1,2,3. "
    "This option is useful when doing multi process training and "
    "each process have only one device (MLU). If you want to use "
    "all visible devices, set this to empty string. NOTE: the "
    "reason of doing this is that we want to use P2P communication"
    "between MLU devices, use MLU_VISIBLE_DEVICES can only use"
    "share-memory only.");

USE_MLU_MEM_STAT;
namespace paddle {
namespace platform {

static int GetMLUDeviceCountImpl() {
  int x, y, z;
  // When cnrtDriverGetVersion is executed, the device is initialized,
  // no longer needs to call cnrtInit().
  cnrtStatus stat = cnrtDriverGetVersion(&x, &y, &z);
  if (stat != cnrtSuccess) {
    VLOG(2) << "MLU Driver Version can't be detected. No MLU driver!";
    return 0;
  }

  const auto *mlu_visible_devices = std::getenv("MLU_VISIBLE_DEVICES");
  if (mlu_visible_devices != nullptr) {
    std::string mlu_visible_devices_str(mlu_visible_devices);
    if (std::all_of(mlu_visible_devices_str.begin(),
                    mlu_visible_devices_str.end(),
                    [](char ch) { return ch == ' '; })) {
      VLOG(2) << "MLU_VISIBLE_DEVICES  is set to be "
                 "empty. No MLU detected.";
      return 0;
    }
  }

  int count;
  PADDLE_ENFORCE_MLU_SUCCESS(cnDeviceGetCount(&count));
  return count;
}

int GetMLUDeviceCount() {
  static auto dev_cnt = GetMLUDeviceCountImpl();
  return dev_cnt;
}

std::vector<int> GetMLUSelectedDevices() {
  // use user specified MLUs in single-node multi-process mode.
  std::vector<int> devices;
  if (!FLAGS_selected_mlus.empty()) {
    auto devices_str = paddle::string::Split(FLAGS_selected_mlus, ',');
    for (auto id : devices_str) {
      devices.push_back(atoi(id.c_str()));
    }
  } else {
    int count = GetMLUDeviceCount();
    for (int i = 0; i < count; ++i) {
      devices.push_back(i);
    }
  }
  return devices;
}

void CheckDeviceId(int id) {
  PADDLE_ENFORCE_LT(id, GetMLUDeviceCount(),
                    platform::errors::InvalidArgument(
                        "Device id must be less than MLU count, "
                        "but received id is: %d. MLU count is: %d.",
                        id, GetMLUDeviceCount()));
}

int GetMLUDriverVersion(int id) {
  CheckDeviceId(id);
  int x, y, z;
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtDriverGetVersion(&x, &y, &z));
  return x * 10000 + y * 100 + z;
}

int GetMLURuntimeVersion(int id) {
  CheckDeviceId(id);
  int x, y, z;
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtGetLibVersion(&x, &y, &z));
  return x * 10000 + y * 100 + z;
}

Q
qipengh 已提交
119 120 121 122 123 124 125
int GetMLUCnnlVersion(int id) {
  CheckDeviceId(id);
  int x, y, z;
  cnnlGetLibVersion(&x, &y, &z);
  return x * 10000 + y * 100 + z;
}

F
fwenguang 已提交
126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
int GetMLUCurrentDeviceId() {
  int device_id;
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtGetDevice(&device_id));
  return device_id;
}

void SetMLUDeviceId(int id) {
  CheckDeviceId(id);
  PADDLE_RETRY_MLU_SUCCESS(cnrtSetDevice(id));
}

void GetMLUDeviceHandle(int device_ordinal, mluDeviceHandle *device) {
  cnStatus res = cnDeviceGet(device, device_ordinal);
  if (res != CN_SUCCESS) {
    VLOG(2) << "failed to get handle of MLU Device.";
  }
  PADDLE_ENFORCE_MLU_SUCCESS(res);
}

int GetMLUComputeCapability(int id) {
  CheckDeviceId(id);
  mluDeviceHandle device;
  GetMLUDeviceHandle(id, &device);

  int major, minor;
  cnStatus major_stat = cnDeviceGetAttribute(
      &major, CN_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, device);
  cnStatus minor_stat = cnDeviceGetAttribute(
      &minor, CN_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, device);
  PADDLE_ENFORCE_MLU_SUCCESS(major_stat);
  PADDLE_ENFORCE_MLU_SUCCESS(minor_stat);

  return major * 10 + minor;
}

void MLUMemoryUsage(size_t *available, size_t *total) {
  size_t actual_available, actual_total;
  RecordedMLUMemGetInfo(available, total, &actual_available, &actual_total,
                        platform::GetMLUCurrentDeviceId());
}

size_t MLUAvailableMemToAlloc() {
  size_t total = 0;
  size_t available = 0;
  MLUMemoryUsage(&available, &total);
  size_t reserving =
      static_cast<size_t>(fraction_reserve_mlu_memory * available);
  // If available size is less than minimum chunk size, no usable memory exists
  size_t available_to_alloc = available - reserving;
  size_t min_chunk_size = MLUMinChunkSize();
  if (available_to_alloc < min_chunk_size) {
    available_to_alloc = 0;
  }
  VLOG(10) << "MLU usage " << ((total - available) >> 20) << "M/"
           << (total >> 20) << "M, " << (available_to_alloc >> 20)
           << "M available to allocate";
  return available_to_alloc;
}

size_t MLUMaxAllocSize() {
  return std::max(MLUInitAllocSize(), MLUReallocSize());
}

static size_t MLUAllocSize(bool realloc) {
  size_t available_to_alloc = MLUAvailableMemToAlloc();
  PADDLE_ENFORCE_GT(
      available_to_alloc, 0,
      platform::errors::ResourceExhausted("Not enough available MLU memory."));
  // If FLAGS_initial_gpu_memory_in_mb is 0, then initial memory will be
  // allocated by fraction
  size_t flag_mb = realloc ? FLAGS_reallocate_gpu_memory_in_mb
                           : FLAGS_initial_gpu_memory_in_mb;
  size_t alloc_bytes =
199 200 201
      (flag_mb > 0ul
           ? flag_mb << 20
           : available_to_alloc * FLAGS_fraction_of_gpu_memory_to_use);
F
fwenguang 已提交
202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436
  PADDLE_ENFORCE_GE(
      available_to_alloc, alloc_bytes,
      platform::errors::ResourceExhausted("Not enough available MLU memory."));
  VLOG(10) << "Alloc size is " << (alloc_bytes >> 20)
           << " MiB, is it Re-alloc: " << realloc;
  return alloc_bytes;
}

size_t MLUInitAllocSize() { return MLUAllocSize(/* realloc = */ false); }

size_t MLUReallocSize() { return MLUAllocSize(/* realloc = */ true); }

size_t MLUMinChunkSize() {
  // Allow to allocate the minimum chunk size is 256 bytes.
  return 1 << 8;
}

size_t MLUMaxChunkSize() {
  size_t max_chunk_size = MLUMaxAllocSize();
  VLOG(10) << "Max chunk size " << (max_chunk_size >> 20) << "M";
  return max_chunk_size;
}

void MLUMemcpyD2HAsync(void *dst, const void *src, size_t num,
                       mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemcpyAsync(dst, const_cast<void *>(src), num,
                                             stream, cnrtMemcpyDevToHost));
}

void MLUMemcpyD2HSync(void *dst, const void *src, size_t num) {
  PADDLE_ENFORCE_MLU_SUCCESS(
      cnrtMemcpy(dst, const_cast<void *>(src), num, cnrtMemcpyDevToHost));
}

void MLUMemcpyH2DAsync(void *dst, const void *src, size_t num,
                       mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemcpyAsync(dst, const_cast<void *>(src), num,
                                             stream, cnrtMemcpyHostToDev));
}
void MLUMemcpyH2DSync(void *dst, const void *src, size_t num) {
  PADDLE_ENFORCE_MLU_SUCCESS(
      cnrtMemcpy(dst, const_cast<void *>(src), num, cnrtMemcpyHostToDev));
}

void MLUMemcpyD2DAsync(void *dst, const void *src, size_t num,
                       mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemcpyAsync(dst, const_cast<void *>(src), num,
                                             stream, cnrtMemcpyDevToDev));
}
void MLUMemcpyD2DSync(void *dst, const void *src, size_t num) {
  PADDLE_ENFORCE_MLU_SUCCESS(
      cnrtMemcpy(dst, const_cast<void *>(src), num, cnrtMemcpyDevToDev));
}

void MLUMemcpyPeerAsync(void *dst, int dst_device, const void *src,
                        int src_device, size_t num, mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemcpyPeerAsync(
      dst, dst_device, const_cast<void *>(src), src_device, num, stream));
}

void MLUMemcpyPeerSync(void *dst, int dst_device, const void *src,
                       int src_device, size_t num) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemcpyPeer(
      dst, dst_device, const_cast<void *>(src), src_device, num));
}

void MLUMemsetAsync(void *dst, int value, size_t count, mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtMemsetAsync(dst, value, count, stream));
}

void MLUStreamSync(mluStream stream) {
  PADDLE_ENFORCE_MLU_SUCCESS(cnrtQueueSync(stream));
}

static void RaiseNonOutOfMemoryError(cnrtStatus *status) {
  if (*status == cnrtErrorNoMem) {
    *status = cnrtSuccess;
  }
  PADDLE_ENFORCE_MLU_SUCCESS(*status);

  *status = cnrtGetLastError();
  if (*status == cnrtErrorNoMem) {
    *status = cnrtSuccess;
  }
  PADDLE_ENFORCE_MLU_SUCCESS(*status);
}

class RecordedMLUMallocHelper {
 private:
  explicit RecordedMLUMallocHelper(int dev_id, uint64_t limit_size = 0)
      : dev_id_(dev_id), limit_size_(limit_size) {
    if (NeedRecord()) {
      mtx_.reset(new std::mutex());
    }
  }

  DISABLE_COPY_AND_ASSIGN(RecordedMLUMallocHelper);

 public:
  static RecordedMLUMallocHelper *Instance(int dev_id) {
    std::call_once(once_flag_, [] {
      int dev_cnt = GetMLUDeviceCount();
      instances_.reserve(dev_cnt);
      for (int i = 0; i < dev_cnt; ++i) {
        instances_.emplace_back(
            new RecordedMLUMallocHelper(i, FLAGS_gpu_memory_limit_mb << 20));
      }
    });

    PADDLE_ENFORCE_GE(
        dev_id, 0,
        platform::errors::OutOfRange(
            "Device id must be not less than 0, but got %d.", dev_id));
    PADDLE_ENFORCE_LT(
        dev_id, instances_.size(),
        platform::errors::OutOfRange("Device id %d exceeds mlu card number %d.",
                                     dev_id, instances_.size()));
    return instances_[dev_id].get();
  }

  /**
   * Try to allocate `size` mlu memory. Only cnrtErrorNoMem
   * or cnrtSuccess would be returned, and the cnrtGetLastError() flag
   * would be clear.
   */
  cnrtStatus Malloc(void **ptr, size_t size) {
    LockGuardPtr<std::mutex> lock(mtx_);
    if (UNLIKELY(NeedRecord() && cur_size_.load() + size > limit_size_)) {
      return cnrtErrorNoMem;
    }

    MLUDeviceGuard guard(dev_id_);
    auto result = cnrtMalloc(ptr, size);
    if (result == cnrtSuccess) {
      cur_size_.fetch_add(size);
      STAT_INT_ADD("STAT_mlu" + std::to_string(dev_id_) + "_mem_size", size);
      return cnrtSuccess;
    } else {
      RaiseNonOutOfMemoryError(&result);
      // Non out of memory error would be raised inside
      // RaiseNonOutOfMemoryError.
      // Therefore, we can return cnrtErrorNoMem directly here.
      return cnrtErrorNoMem;
    }
  }

  /**
   * Free mlu memory. Usually, free is not allowed to raise error.
   * If it does raise error, the process should be crashed.
   */
  void Free(void *ptr, size_t size) {
    MLUDeviceGuard guard(dev_id_);
    auto err = cnrtFree(ptr);
    PADDLE_ENFORCE_MLU_SUCCESS(err);
    if (NeedRecord()) {
      cur_size_.fetch_sub(size);
    }
    STAT_INT_SUB("STAT_mlu" + std::to_string(dev_id_) + "_mem_size", size);
  }

  bool GetMemInfo(size_t *avail, size_t *total, size_t *actual_avail,
                  size_t *actual_total) {
    {
      MLUDeviceGuard guard(dev_id_);
      auto result = cnrtMemGetInfo(actual_avail, actual_total);
      if (result != cnrtSuccess) {
        *actual_avail = 0;
      }
      RaiseNonOutOfMemoryError(&result);
    }

    if (NeedRecord()) {
      std::lock_guard<std::mutex> guard(*mtx_);
      *avail = std::min(*actual_avail, limit_size_ - cur_size_.load());
      *total = std::min(*actual_total, limit_size_);
      return *total < *actual_total;
    } else {
      *avail = *actual_avail;
      *total = *actual_total;
      return false;
    }
  }

  inline bool NeedRecord() const { return limit_size_ != 0; }

  uint64_t RecordedSize() const { return cur_size_.load(); }

  uint64_t LimitSize() const { return limit_size_; }

 private:
  const int dev_id_;
  const uint64_t limit_size_;
  std::atomic<uint64_t> cur_size_{0};

  mutable std::unique_ptr<std::mutex> mtx_;

  static std::once_flag once_flag_;
  static std::vector<std::unique_ptr<RecordedMLUMallocHelper>> instances_;
};  // NOLINT

std::once_flag RecordedMLUMallocHelper::once_flag_;
std::vector<std::unique_ptr<RecordedMLUMallocHelper>>
    RecordedMLUMallocHelper::instances_;

cnrtStatus RecordedMLUMalloc(void **ptr, size_t size, int dev_id) {
  return RecordedMLUMallocHelper::Instance(dev_id)->Malloc(ptr, size);
}

void RecordedMLUFree(void *p, size_t size, int dev_id) {
  return RecordedMLUMallocHelper::Instance(dev_id)->Free(p, size);
}

bool RecordedMLUMemGetInfo(size_t *avail, size_t *total, size_t *actual_avail,
                           size_t *actual_total, int dev_id) {
  return RecordedMLUMallocHelper::Instance(dev_id)->GetMemInfo(
      avail, total, actual_avail, actual_total);
}

uint64_t RecordedMLUMallocSize(int dev_id) {
  return RecordedMLUMallocHelper::Instance(dev_id)->RecordedSize();
}

bool IsMLUMallocRecorded(int dev_id) {
  return RecordedMLUMallocHelper::Instance(dev_id)->NeedRecord();
}

void EmptyCache(void) {
  std::vector<int> devices = GetMLUSelectedDevices();
  for (auto device : devices) {
    memory::Release(MLUPlace(device));
  }
}

}  // namespace platform
}  // namespace paddle