change sample result's structure to fit training (PaddlePaddle#42426)

* enable graph-engine to return all id

* change vector's dimension

* change vector's dimension

* enlarge returned ids dimensions

* add actual_val

* change vlog

* fix bug

* bug fix

* bug fix

* fix display test

* singleton of gpu_graph_wrapper

* change sample result's structure to fit training

* recover sample code

* fix

* secondary sample

* add graph partition

* fix pybind

Co-authored-by: DesmonDay <[email protected]>

paddle/fluid/distributed/ps/table/common_graph_table.h

@@ -426,6 +426,10 @@ class GraphTable : public Table {
     use_cache = false;
     shard_num = 0;
     rw_lock.reset(new pthread_rwlock_t());
+#ifdef PADDLE_WITH_HETERPS
+    next_partition = 0;
+    total_memory_cost = 0;
+#endif
   }
   virtual ~GraphTable();
 
@@ -521,7 +525,7 @@ class GraphTable : public Table {
       const std::vector<std::vector<std::string>> &res);
 
   size_t get_server_num() { return server_num; }
-
+  void clear_graph(int idx);
   virtual int32_t make_neighbor_sample_cache(size_t size_limit, size_t ttl) {
     {
       std::unique_lock<std::mutex> lock(mutex_);
@@ -546,15 +550,33 @@ class GraphTable : public Table {
   //   graph_sampler->set_graph_sample_callback(callback);
   //   return 0;
   // }
+  virtual void make_partitions(int idx, int64_t gb_size, int device_len);
   virtual char *random_sample_neighbor_from_ssd(
       int idx, int64_t id, int sample_size,
       const std::shared_ptr<std::mt19937_64> rng, int &actual_size);
   virtual int32_t add_node_to_ssd(int type_id, int idx, int64_t src_id,
                                   char *data, int len);
   virtual paddle::framework::GpuPsCommGraph make_gpu_ps_graph(
       int idx, std::vector<int64_t> ids);
+  int32_t Load_to_ssd(const std::string &path, const std::string &param);
+  int64_t load_graph_to_memory_from_ssd(int idx, std::vector<int64_t> &ids);
+  int32_t make_complementary_graph(int idx, int64_t byte_size);
+  int32_t dump_edges_to_ssd(int idx);
+  int32_t get_partition_num(int idx) { return partitions[idx].size(); }
+  std::vector<int64_t> get_partition(int idx, int index) {
+    if (idx >= partitions.size() || index >= partitions[idx].size())
+      return std::vector<int64_t>();
+    return partitions[idx][index];
+  }
+  int32_t load_edges_to_ssd(const std::string &path, bool reverse_edge,
+                            const std::string &edge_type);
+  int32_t load_next_partition(int idx);
+  void set_search_level(int search_level) { this->search_level = search_level; }
   // virtual GraphSampler *get_graph_sampler() { return graph_sampler.get(); }
   int search_level;
+  int64_t total_memory_cost;
+  std::vector<std::vector<std::vector<int64_t>>> partitions;
+  int next_partition;
 #endif
   virtual int32_t add_comm_edge(int idx, int64_t src_id, int64_t dst_id);
   virtual int32_t build_sampler(int idx, std::string sample_type = "random");

paddle/fluid/framework/fleet/heter_ps/gpu_graph_node.h

@@ -24,36 +24,46 @@ namespace paddle {
 namespace framework {
 struct GpuPsGraphNode {
   int64_t node_id;
-  int neighbor_size, neighbor_offset;
+  unsigned int neighbor_size, neighbor_offset;
   // this node's neighbor is stored on [neighbor_offset,neighbor_offset +
   // neighbor_size) of int64_t *neighbor_list;
 };
 
 struct GpuPsCommGraph {
   int64_t *neighbor_list;
   GpuPsGraphNode *node_list;
-  int neighbor_size, node_size;
+  unsigned int neighbor_size, node_size;
   // the size of neighbor array and graph_node_list array
   GpuPsCommGraph()
       : neighbor_list(NULL), node_list(NULL), neighbor_size(0), node_size(0) {}
   GpuPsCommGraph(int64_t *neighbor_list_, GpuPsGraphNode *node_list_,
-                 int neighbor_size_, int node_size_)
+                 unsigned int neighbor_size_, unsigned int node_size_)
       : neighbor_list(neighbor_list_),
         node_list(node_list_),
         neighbor_size(neighbor_size_),
         node_size(node_size_) {}
+  void init_on_cpu(unsigned int neighbor_size, unsigned int node_size) {
+    this->neighbor_size = neighbor_size;
+    this->node_size = node_size;
+    this->neighbor_list = new int64_t[neighbor_size];
+    this->node_list = new paddle::framework::GpuPsGraphNode[node_size];
+  }
+  void release_on_cpu() {
+    delete[] neighbor_list;
+    delete[] node_list;
+  }
   void display_on_cpu() {
     VLOG(0) << "neighbor_size = " << neighbor_size;
     VLOG(0) << "node_size = " << node_size;
-    for (int i = 0; i < neighbor_size; i++) {
+    for (size_t i = 0; i < neighbor_size; i++) {
       VLOG(0) << "neighbor " << i << " " << neighbor_list[i];
     }
-    for (int i = 0; i < node_size; i++) {
+    for (size_t i = 0; i < node_size; i++) {
       VLOG(0) << "node i " << node_list[i].node_id
               << " neighbor_size = " << node_list[i].neighbor_size;
       std::string str;
       int offset = node_list[i].neighbor_offset;
-      for (int j = 0; j < node_list[i].neighbor_size; j++) {
+      for (size_t j = 0; j < node_list[i].neighbor_size; j++) {
         if (j > 0) str += ",";
         str += std::to_string(neighbor_list[j + offset]);
       }
@@ -139,12 +149,18 @@ struct NeighborSampleQuery {
 };
 struct NeighborSampleResult {
   int64_t *val;
+  int64_t *actual_val;
   int *actual_sample_size, sample_size, key_size;
+  int total_sample_size;
   std::shared_ptr<memory::Allocation> val_mem, actual_sample_size_mem;
+  std::shared_ptr<memory::Allocation> actual_val_mem;
   int64_t *get_val() { return val; }
+  int64_t get_actual_val() { return (int64_t)actual_val; }
   int *get_actual_sample_size() { return actual_sample_size; }
   int get_sample_size() { return sample_size; }
   int get_key_size() { return key_size; }
+  void set_total_sample_size(int s) { total_sample_size = s; }
+  int get_len() { return total_sample_size; }
   void initialize(int _sample_size, int _key_size, int dev_id) {
     sample_size = _sample_size;
     key_size = _key_size;
@@ -165,18 +181,30 @@ struct NeighborSampleResult {
     int *ac_size = new int[key_size];
     cudaMemcpy(ac_size, actual_sample_size, key_size * sizeof(int),
                cudaMemcpyDeviceToHost);  // 3, 1, 3
+    int total_sample_size = 0;
+    for (int i = 0; i < key_size; i++) {
+      total_sample_size += ac_size[i];
+    }
+    int64_t *res2 = new int64_t[total_sample_size];  // r
+    cudaMemcpy(res2, actual_val, total_sample_size * sizeof(int64_t),
+               cudaMemcpyDeviceToHost);  // r
 
+    int start = 0;
     for (int i = 0; i < key_size; i++) {
       VLOG(0) << "actual sample size for " << i << "th key is " << ac_size[i];
       VLOG(0) << "sampled neighbors are ";
-      std::string neighbor;
+      std::string neighbor, neighbor2;
       for (int j = 0; j < ac_size[i]; j++) {
-        if (neighbor.size() > 0) neighbor += ";";
-        neighbor += std::to_string(res[i * sample_size + j]);
+        // if (neighbor.size() > 0) neighbor += ";";
+        if (neighbor2.size() > 0) neighbor2 += ";";  // r
+        // neighbor += std::to_string(res[i * sample_size + j]);
+        neighbor2 += std::to_string(res2[start + j]);  // r
       }
-      VLOG(0) << neighbor;
+      VLOG(0) << neighbor << " " << neighbor2;
+      start += ac_size[i];  // r
     }
     delete[] res;
+    delete[] res2;  // r
     delete[] ac_size;
     VLOG(0) << " ------------------";
   }

paddle/fluid/framework/fleet/heter_ps/graph_gpu_ps_table.h

@@ -23,13 +23,18 @@
 #ifdef PADDLE_WITH_HETERPS
 namespace paddle {
 namespace framework {
-class GpuPsGraphTable : public HeterComm<int64_t, int, int> {
+class GpuPsGraphTable : public HeterComm<int64_t, unsigned int, int> {
  public:
   GpuPsGraphTable(std::shared_ptr<HeterPsResource> resource, int topo_aware)
-      : HeterComm<int64_t, int, int>(1, resource) {
+      : HeterComm<int64_t, unsigned int, int>(1, resource) {
     load_factor_ = 0.25;
     rw_lock.reset(new pthread_rwlock_t());
     gpu_num = resource_->total_device();
+    for (int i = 0; i < gpu_num; i++) {
+      gpu_graph_list.push_back(GpuPsCommGraph());
+      sample_status.push_back(NULL);
+      tables_.push_back(NULL);
+    }
     cpu_table_status = -1;
     if (topo_aware) {
       int total_gpu = resource_->total_device();
@@ -82,6 +87,8 @@ class GpuPsGraphTable : public HeterComm<int64_t, int, int> {
     //   end_graph_sampling();
     // }
   }
+  void build_graph_on_single_gpu(GpuPsCommGraph &g, int gpu_id);
+  void clear_graph_info(int gpu_id);
   void build_graph_from_cpu(std::vector<GpuPsCommGraph> &cpu_node_list);
   NodeQueryResult graph_node_sample(int gpu_id, int sample_size);
   NeighborSampleResult graph_neighbor_sample_v3(NeighborSampleQuery q,