【发布时间】:2020-08-09 19:50:19
【问题描述】:
我正在尝试将字典集合合并到根进程中。这是一个简短的例子:
#define MAX_CF_LENGTH 55
map<string, int> dict;
if (rank == 0)
{
dict = {
{"Accelerator Defective", 33},
{"Aggressive Driving/Road Rage", 27},
{"Alcohol Involvement", 19},
{"Animals Action", 30}};
}
if (rank == 1)
{
dict = {
{"Driver Inexperience", 6},
{"Driverless/Runaway Vehicle", 46},
{"Drugs (Illegal)", 38},
{"Failure to Keep Right", 24}};
}
if (rank == 2)
{
dict = {
{"Lost Consciousness", 1},
{"Obstruction/Debris", 8},
{"Other Electronic Device", 25},
{"Other Lighting Defects", 43},
{"Other Vehicular", 7}};
}
Scatterer scatterer(rank, MPI_COMM_WORLD, num_workers);
scatterer.gatherDictionary(dict, MAX_CF_LENGTH);
gatherDictionary() 内部的想法是将每个键放在每个进程的char 数组中(允许重复)。之后,将所有键收集到根中并在广播之前创建最终(合并)字典。代码如下:
void Scatterer::gatherDictionary(map<string,int> &dict, int maxKeyLength)
{
// Calculate destination dictionary size
int numKeys = dict.size();
int totalLength = numKeys * maxKeyLength;
int finalNumKeys = 0;
MPI_Reduce(&numKeys, &finalNumKeys, 1, MPI_INT, MPI_SUM, 0, comm);
// Computing number of elements that are received from each process
int *recvcounts = NULL;
if (rank == 0)
recvcounts = new int[num_workers];
MPI_Gather(&totalLength, 1, MPI_INT, recvcounts, 1, MPI_INT, 0, comm);
// Computing displacement relative to recvbuf at which to place the incoming data from each process
int *displs = NULL;
if (rank == 0)
{
displs = new int[num_workers];
displs[0] = 0;
for (int i = 1; i < num_workers; i++)
displs[i] = displs[i - 1] + recvcounts[i - 1] + 1;
}
char(*dictKeys)[maxKeyLength];
char(*finalDictKeys)[maxKeyLength];
dictKeys = (char(*)[maxKeyLength])malloc(numKeys * sizeof(*dictKeys));
if (rank == 0)
finalDictKeys = (char(*)[maxKeyLength])malloc(finalNumKeys * sizeof(*finalDictKeys));
// Collect keys for each process
int i = 0;
for (auto pair : dict)
{
strncpy(dictKeys[i], pair.first.c_str(), maxKeyLength);
i++;
}
MPI_Gatherv(dictKeys, totalLength, MPI_CHAR, finalDictKeys, recvcounts, displs, MPI_CHAR, 0, comm);
// Create new dictionary and distribute it to all processes
dict.clear();
if (rank == 0)
{
for (int i = 0; i < finalNumKeys; i++)
dict[finalDictKeys[i]] = dict.size();
}
delete[] dictKeys;
if (rank == 0)
{
delete[] finalDictKeys;
delete[] recvcounts;
delete[] displs;
}
broadcastDictionary(dict, maxKeyLength);
}
我确信broadcastDicitonary() 的正确性,因为我已经对其进行了测试。调试收集功能,我得到以下部分结果:
Recvcounts:
220
220
275
Displacements:
0
221
442
FinalDictKeys:
Rank:0 Accelerator Defective
Rank:0 Aggressive Driving/Road Rage
Rank:0 Alcohol Involvement
Rank:0 Animals Action
Rank:0
Rank:0
Rank:0
Rank:0
Rank:0
Rank:0
Rank:0
Rank:0
Rank:0
由于只收集根数据,我想知道这是否与字符分配有关,即使它应该是连续的。我不认为这与最后缺少空字符有关,因为每个字符串/键已经有很多填充。 提前感谢您指出任何缺失或改进,如果您需要任何额外信息,请发表评论。
如果您想自己测试它,我已将所有代码放在一个文件中,它已准备好编译和运行(当然这适用于 3 个 mpi 进程)。 Code Here
【问题讨论】:
-
它在第一行中说明,但为了清楚起见,我已将其添加到参数列表中。感谢您指出。
-
displs[i] = displs[i - 1] + recvcounts[i - 1] + 1;为什么最后是+1? -
感谢您的建议。代码有很多依赖关系,所以我只把必需品放在一起粘贴。添加链接。
-
@DanielLangr 因为计数例如是 220,所以我认为下一个位移应该从 221 等开始。没有考虑到我实际上是从 0 开始的事实......这相当尴尬,因为
+1改变了一切。非常感谢。 -
是的,确实如此。如果它不是性能关键的收集广播组合,那么你可能没问题。如果代码应该运行在具有数万或数十万个 MPI 进程的大型超级计算机上,那么我会根据条件选择运行
MPI_Gatherv或MPI_Allgatherv。