cache optimization

Author: seemingwang

paddle/fluid/distributed/table/common_graph_table.h

@@ -105,8 +105,6 @@ class LRUNode {
  LRUNode(K _key, V _data, size_t _ttl) : key(_key), data(_data), ttl(_ttl) {
  next = pre = NULL;
  }
- std::chrono::milliseconds ms;
- // the last hit time
  K key;
  V data;
  size_t ttl;
@@ -119,12 +117,13 @@ class ScaledLRU;
 template <typename K, typename V>
 class RandomSampleLRU {
  public:
- RandomSampleLRU(ScaledLRU<K, V> *_father) : father(_father) {
+ RandomSampleLRU(ScaledLRU<K, V> *_father) {
+ father = _father;
+ remove_count = 0;
  node_size = 0;
  node_head = node_end = NULL;
  global_ttl = father->ttl;
- extra_penalty = 0;
- size_limit = (father->size_limit / father->shard_num + 1);
+ total_diff = 0;
  }
 
  ~RandomSampleLRU() {
@@ -138,63 +137,71 @@ class RandomSampleLRU {
  LRUResponse query(K *keys, size_t length, std::vector<std::pair<K, V>> &res) {
  if (pthread_rwlock_tryrdlock(&father->rwlock) != 0)
  return LRUResponse::blocked;
- int init_node_size = node_size;
- try {
- // pthread_rwlock_rdlock(&father->rwlock);
- for (size_t i = 0; i < length; i++) {
- auto iter = key_map.find(keys[i]);
- if (iter != key_map.end()) {
- res.emplace_back(keys[i], iter->second->data);
- iter->second->ttl--;
- if (iter->second->ttl == 0) {
- remove(iter->second);
- } else {
- move_to_tail(iter->second);
- }
+ // pthread_rwlock_rdlock(&father->rwlock);
+ int init_size = node_size - remove_count;
+ process_redundant(length * 3);
+
+ for (size_t i = 0; i < length; i++) {
+ auto iter = key_map.find(keys[i]);
+ if (iter != key_map.end()) {
+ res.emplace_back(keys[i], iter->second->data);
+ iter->second->ttl--;
+ if (iter->second->ttl == 0) {
+ remove(iter->second);
+ if (remove_count != 0) remove_count--;
+ } else {
+ move_to_tail(iter->second);
  }
  }
- } catch (...) {
- pthread_rwlock_unlock(&father->rwlock);
- father->handle_size_diff(node_size - init_node_size);
- return LRUResponse::err;
+ }
+ total_diff += node_size - remove_count - init_size;
+ if (total_diff >= 500 || total_diff < -500) {
+ father->handle_size_diff(total_diff);
+ total_diff = 0;
  }
  pthread_rwlock_unlock(&father->rwlock);
- father->handle_size_diff(node_size - init_node_size);
  return LRUResponse::ok;
  }
  LRUResponse insert(K *keys, V *data, size_t length) {
  if (pthread_rwlock_tryrdlock(&father->rwlock) != 0)
  return LRUResponse::blocked;
- int init_node_size = node_size;
- try {
-  for (size_t i = 0; i < length; i++) {
-  auto iter = key_map.find(keys[i]);
-  if (iter != key_map.end()) {
-  move_to_tail(iter->second);
-  iter->second->ttl = global_ttl;
-  iter->second->data = data[i];
- } else {
-  LRUNode<K, V> *temp = new LRUNode<K, V>(keys[i], data[i], global_ttl);
-  add_new(temp);
- }
+ // pthread_rwlock_rdlock(&father->rwlock);
+ int init_size = node_size - remove_count;
+ process_redundant(length * 3);
+ for (size_t i = 0; i < length; i++) {
+ auto iter = key_map.find(keys[i]);
+ if (iter != key_map.end()) {
+ move_to_tail(iter->second);
+ iter->second->ttl = global_ttl;
+ iter->second->data = data[i];
+ } else {
+ LRUNode<K, V> *temp = new LRUNode<K, V>(keys[i], data[i], global_ttl);
+ add_new(temp);
  }
- } catch (...) {
- pthread_rwlock_unlock(&father->rwlock);
- father->handle_size_diff(node_size - init_node_size);
- return LRUResponse::err;
  }
+ total_diff += node_size - remove_count - init_size;
+ if (total_diff >= 500 || total_diff < -500) {
+ father->handle_size_diff(total_diff);
+ total_diff = 0;
+ }
+
  pthread_rwlock_unlock(&father->rwlock);
- father->handle_size_diff(node_size - init_node_size);
  return LRUResponse::ok;
  }
  void remove(LRUNode<K, V> *node) {
  fetch(node);
  node_size--;
  key_map.erase(node->key);
  delete node;
- if (node_size >= size_limit) {
- extra_penalty -= 1.0;
+ }
+
+ void process_redundant(int process_size) {
+ size_t length = std::min(remove_count, process_size);
+ while (length--) {
+ remove(node_head);
+ remove_count--;
  }
+ // std::cerr<<"after remove_count = "<<remove_count<<std::endl;
  }
 
  void move_to_tail(LRUNode<K, V> *node) {
@@ -207,12 +214,6 @@ class RandomSampleLRU {
  place_at_tail(node);
  node_size++;
  key_map[node->key] = node;
- if (node_size > size_limit) {
- extra_penalty += penalty_inc;
- if (extra_penalty >= 1.0) {
- remove(node_head);
- }
- }
  }
  void place_at_tail(LRUNode<K, V> *node) {
  if (node_end == NULL) {
@@ -224,8 +225,6 @@ class RandomSampleLRU {
  node->next = NULL;
  node_end = node;
  }
- node->ms = std::chrono::duration_cast<std::chrono::milliseconds>(
- std::chrono::system_clock::now().time_since_epoch());
  }
 
  void fetch(LRUNode<K, V> *node) {
@@ -245,11 +244,10 @@ class RandomSampleLRU {
  std::unordered_map<K, LRUNode<K, V> *> key_map;
  ScaledLRU<K, V> *father;
  size_t global_ttl, size_limit;
- int node_size;
+ int node_size, total_diff;
  LRUNode<K, V> *node_head, *node_end;
  friend class ScaledLRU<K, V>;
- float extra_penalty;
- const float penalty_inc = 0.75;
+ int remove_count;
 };
 
 template <typename K, typename V>
@@ -268,7 +266,7 @@ class ScaledLRU {
  while (true) {
  {
  std::unique_lock<std::mutex> lock(mutex_);
- cv_.wait_for(lock, std::chrono::milliseconds(20000));
+ cv_.wait_for(lock, std::chrono::milliseconds(3000));
  if (stop) {
  return;
  }
@@ -295,52 +293,33 @@ class ScaledLRU {
  int shrink() {
  int node_size = 0;
  for (size_t i = 0; i < lru_pool.size(); i++) {
- node_size += lru_pool[i].node_size;
+ node_size += lru_pool[i].node_size - lru_pool[i].remove_count;
  }
 
- if (node_size <= 1.2 * size_limit) return 0;
+ if (node_size <= size_t(1.1 * size_limit) + 1) return 0;
  if (pthread_rwlock_wrlock(&rwlock) == 0) {
- try {
- global_count = 0;
- std::priority_queue<RemovedNode, std::vector<RemovedNode>,
- std::greater<RemovedNode>>
- q;
- for (size_t i = 0; i < lru_pool.size(); i++) {
- if (lru_pool[i].node_size > 0) {
- global_count += lru_pool[i].node_size;
- q.push({lru_pool[i].node_head, &lru_pool[i]});
- }
- }
- if (global_count > size_limit) {
- // VLOG(0)<<"before shrinking cache, cached nodes count =
- // "<<global_count<<std::endl;
- size_t remove = global_count - size_limit;
- while (remove--) {
- RemovedNode remove_node = q.top();
- q.pop();
- auto next = remove_node.node->next;
- if (next) {
- q.push({next, remove_node.lru_pointer});
- }
- global_count--;
- remove_node.lru_pointer->remove(remove_node.node);
- }
- for (size_t i = 0; i < lru_pool.size(); i++) {
- lru_pool[i].size_limit = lru_pool[i].node_size;
- lru_pool[i].extra_penalty = 0;
- }
- // VLOG(0)<<"after shrinking cache, cached nodes count =
- // // "<<global_count<<std::endl;
+ // std::cerr<<"in shrink\n";
+ global_count = 0;
+ for (size_t i = 0; i < lru_pool.size(); i++) {
+ global_count += lru_pool[i].node_size - lru_pool[i].remove_count;
+ }
+ // std::cerr<<"global_count "<<global_count<<"\n";
+ if (global_count > size_limit) {
+ size_t remove = global_count - size_limit;
+ for (int i = 0; i < lru_pool.size(); i++) {
+ lru_pool[i].total_diff = 0;
+ lru_pool[i].remove_count +=
+ 1.0 * (lru_pool[i].node_size - lru_pool[i].remove_count) /
+ global_count * remove;
+ // std::cerr<<i<<" "<<lru_pool[i].remove_count<<std::endl;
  }
- } catch (...) {
- pthread_rwlock_unlock(&rwlock);
- return -1;
  }
  pthread_rwlock_unlock(&rwlock);
  return 0;
  }
  return 0;
  }
+
  void handle_size_diff(int diff) {
  if (diff != 0) {
  __sync_fetch_and_add(&global_count, diff);
@@ -358,18 +337,13 @@ class ScaledLRU {
  pthread_rwlock_t rwlock;
  size_t shard_num;
  int global_count;
- size_t size_limit;
+ size_t size_limit, total, hit;
  size_t ttl;
  bool stop;
  std::thread shrink_job;
  std::vector<RandomSampleLRU<K, V>> lru_pool;
  mutable std::mutex mutex_;
  std::condition_variable cv_;
- struct RemovedNode {
- LRUNode<K, V> *node;
- RandomSampleLRU<K, V> *lru_pointer;
- bool operator>(const RemovedNode &a) const { return node->ms > a.node->ms; }
- };
  std::shared_ptr<::ThreadPool> thread_pool;
  friend class RandomSampleLRU<K, V>;
 };
@@ -448,13 +422,46 @@ class GraphTable : public SparseTable {
  std::unique_lock<std::mutex> lock(mutex_);
  if (use_cache == false) {
  scaled_lru.reset(new ScaledLRU<SampleKey, SampleResult>(
- shard_end - shard_start, size_limit, ttl));
+ task_pool_size_, size_limit, ttl));
  use_cache = true;
  }
  }
  return 0;
  }
 
+ virtual int32_t test_sample_with_cache(int size, int batch_size,
+ int sample_size) {
+ std::vector<int> actual_sizes1, actual_sizes2;
+ std::vector<std::shared_ptr<char>> buffers1, buffers2;
+ std::vector<uint64_t> node_ids1(batch_size), node_ids2;
+ for (int i = 0; i <= size - batch_size; i += batch_size) {
+ for (int j = 0; j < batch_size; j++) {
+ node_ids1[j] = i + j;
+ }
+ actual_sizes1.resize(batch_size);
+ buffers1.resize(batch_size);
+ random_sample_neighbors(node_ids1.data(), sample_size, buffers1,
+ actual_sizes1);
+ node_ids2.clear();
+ for (int j = 0; j < batch_size; j++) {
+ if (actual_sizes1[j] != 0) {
+ int offset = 0;
+ char *p = buffers1[j].get();
+ while (offset < actual_sizes1[j]) {
+ node_ids2.push_back(*(uint64_t *)(p + offset));
+ offset += Node::id_size + Node::weight_size;
+ }
+ }
+ }
+ buffers2.resize(node_ids2.size());
+ actual_sizes2.resize(node_ids2.size());
+ random_sample_neighbors(node_ids2.data(), sample_size, buffers2,
+ actual_sizes2);
+ }
+
+ return 0;
+ }
+
  protected:
  std::vector<GraphShard> shards;
  size_t shard_start, shard_end, server_num, shard_num_per_server, shard_num;

paddle/fluid/distributed/test/graph_node_test.cc

@@ -1,11 +1,8 @@
 /* Copyright (c) 2020 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.
@@ -681,28 +678,6 @@ void testCache() {
  }
  st.query(0, &skey, 1, r);
  ASSERT_EQ((int)r.size(), 0);
- ::paddle::distributed::ScaledLRU<::paddle::distributed::SampleKey,
- ::paddle::distributed::SampleResult>
- cache1(2, 1, 4);
- str = new char[18];
- strcpy(str, "3433776521");
- result = new ::paddle::distributed::SampleResult(strlen(str), str);
- cache1.insert(1, &skey, result, 1);
- ::paddle::distributed::SampleKey skey1 = {8, 1};
- char* str1 = new char[18];
- strcpy(str1, "3xcf2eersfd");
- usleep(3000); // sleep 3ms to guaruntee that skey1's time stamp is larger
- // than skey;
- auto result1 = new ::paddle::distributed::SampleResult(strlen(str1), str1);
- cache1.insert(0, &skey1, result1, 1);
- sleep(1); // sleep 1 s to guarantee that shrinking work is done
- cache1.query(1, &skey, 1, r);
- ASSERT_EQ((int)r.size(), 0);
- cache1.query(0, &skey1, 1, r);
- ASSERT_EQ((int)r.size(), 1);
- char* p1 = (char*)r[0].second.buffer.get();
- for (int j = 0; j < r[0].second.actual_size; j++) ASSERT_EQ(p1[j], str1[j]);
- r.clear();
 }
 void testGraphToBuffer() {
  ::paddle::distributed::GraphNode s, s1;
@@ -718,4 +693,4 @@ void testGraphToBuffer() {
  VLOG(0) << s1.get_feature(0);
 }
 
-TEST(RunBrpcPushSparse, Run) { RunBrpcPushSparse(); }
+TEST(RunBrpcPushSparse, Run) { RunBrpcPushSparse(); }