Create an implementation file of the Tuples

This commit is contained in:
Alejandro Gallo 2022-10-03 17:11:49 +02:00
parent 2cbff5c8c9
commit fa1a29c583
2 changed files with 475 additions and 430 deletions

View File

@ -52,43 +52,7 @@ struct TuplesDistribution {
// Distributing the tuples:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Node%20information][Node information:1]]
std::vector<std::string> getNodeNames(MPI_Comm comm){
int rank, np;
MPI_Comm_rank(comm, &rank);
MPI_Comm_size(comm, &np);
std::vector<std::string> nodeList(np);
char nodeName[MPI_MAX_PROCESSOR_NAME];
char *nodeNames = (char*)malloc(np * MPI_MAX_PROCESSOR_NAME);
std::vector<int> nameLengths(np)
, off(np)
;
int nameLength;
MPI_Get_processor_name(nodeName, &nameLength);
MPI_Allgather(&nameLength,
1,
MPI_INT,
nameLengths.data(),
1,
MPI_INT,
comm);
for (int i(1); i < np; i++)
off[i] = off[i-1] + nameLengths[i-1];
MPI_Allgatherv(nodeName,
nameLengths[rank],
MPI_BYTE,
nodeNames,
nameLengths.data(),
off.data(),
MPI_BYTE,
comm);
for (int i(0); i < np; i++) {
std::string const s(&nodeNames[off[i]], nameLengths[i]);
nodeList[i] = s;
}
std::free(nodeNames);
return nodeList;
}
std::vector<std::string> getNodeNames(MPI_Comm comm);
// Node information:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Node%20information][Node information:2]]
@ -100,118 +64,28 @@ struct RankInfo {
const size_t ranksPerNode;
};
template <typename A>
A unique(A const &xs) {
auto result = xs;
std::sort(std::begin(result), std::end(result));
auto const& last = std::unique(std::begin(result), std::end(result));
result.erase(last, std::end(result));
return result;
}
std::vector<RankInfo>
getNodeInfos(std::vector<string> const& nodeNames) {
std::vector<RankInfo> result;
auto const uniqueNames = unique(nodeNames);
auto const index = [&uniqueNames](std::string const& s) {
auto const& it = std::find(uniqueNames.begin(), uniqueNames.end(), s);
return std::distance(uniqueNames.begin(), it);
};
std::vector<size_t> localRanks(uniqueNames.size(), 0);
size_t globalRank = 0;
for (auto const& name: nodeNames) {
const size_t nodeId = index(name);
result.push_back({name,
nodeId,
globalRank++,
localRanks[nodeId]++,
(size_t)
std::count(nodeNames.begin(),
nodeNames.end(),
name)
});
}
return result;
}
getNodeInfos(std::vector<string> const& nodeNames);
struct ClusterInfo {
const size_t nNodes, np, ranksPerNode;
const std::vector<RankInfo> rankInfos;
};
ClusterInfo
getClusterInfo(MPI_Comm comm) {
auto const names = getNodeNames(comm);
auto const rankInfos = getNodeInfos(names);
return ClusterInfo {
unique(names).size(),
names.size(),
rankInfos[0].ranksPerNode,
rankInfos
};
}
ClusterInfo getClusterInfo(MPI_Comm comm);
// Node information:2 ends here
// [[file:~/cuda/atrip/atrip.org::*Naive%20list][Naive list:1]]
ABCTuples getTuplesList(size_t Nv, size_t rank, size_t np) {
const size_t
// total number of tuples for the problem
n = Nv * (Nv + 1) * (Nv + 2) / 6 - Nv
// all ranks should have the same number of tuples_per_rank
, tuples_per_rank = n / np + size_t(n % np != 0)
// start index for the global tuples list
, start = tuples_per_rank * rank
// end index for the global tuples list
, end = tuples_per_rank * (rank + 1)
;
LOG(1,"Atrip") << "tuples_per_rank = " << tuples_per_rank << "\n";
WITH_RANK << "start, end = " << start << ", " << end << "\n";
ABCTuples result(tuples_per_rank, FAKE_TUPLE);
for (size_t a(0), r(0), g(0); a < Nv; a++)
for (size_t b(a); b < Nv; b++)
for (size_t c(b); c < Nv; c++){
if ( a == b && b == c ) continue;
if ( start <= g && g < end) result[r++] = {a, b, c};
g++;
}
return result;
}
ABCTuples getTuplesList(size_t Nv, size_t rank, size_t np);
// Naive list:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Naive%20list][Naive list:2]]
ABCTuples getAllTuplesList(const size_t Nv) {
const size_t n = Nv * (Nv + 1) * (Nv + 2) / 6 - Nv;
ABCTuples result(n);
for (size_t a(0), u(0); a < Nv; a++)
for (size_t b(a); b < Nv; b++)
for (size_t c(b); c < Nv; c++){
if ( a == b && b == c ) continue;
result[u++] = {a, b, c};
}
return result;
}
ABCTuples getAllTuplesList(const size_t Nv);
// Naive list:2 ends here
// [[file:~/cuda/atrip/atrip.org::*Naive%20list][Naive list:3]]
struct NaiveDistribution : public TuplesDistribution {
ABCTuples getTuples(size_t Nv, MPI_Comm universe) override {
int rank, np;
MPI_Comm_rank(universe, &rank);
MPI_Comm_size(universe, &np);
return getTuplesList(Nv, (size_t)rank, (size_t)np);
}
ABCTuples getTuples(size_t Nv, MPI_Comm universe) override;
};
// Naive list:3 ends here
@ -224,19 +98,12 @@ namespace group_and_sort {
// Right now we distribute the slices in a round robin fashion
// over the different nodes (NOTE: not mpi ranks but nodes)
inline
size_t isOnNode(size_t tuple, size_t nNodes) { return tuple % nNodes; }
size_t isOnNode(size_t tuple, size_t nNodes);
// return the node (or all nodes) where the elements of this
// tuple are located
std::vector<size_t> getTupleNodes(ABCTuple const& t, size_t nNodes) {
std::vector<size_t>
nTuple = { isOnNode(t[0], nNodes)
, isOnNode(t[1], nNodes)
, isOnNode(t[2], nNodes)
};
return unique(nTuple);
}
std::vector<size_t> getTupleNodes(ABCTuple const& t, size_t nNodes);
struct Info {
size_t nNodes;
@ -245,302 +112,16 @@ struct Info {
// Utils:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Distribution][Distribution:1]]
ABCTuples specialDistribution(Info const& info, ABCTuples const& allTuples) {
ABCTuples nodeTuples;
size_t const nNodes(info.nNodes);
std::vector<ABCTuples>
container1d(nNodes)
, container2d(nNodes * nNodes)
, container3d(nNodes * nNodes * nNodes)
;
WITH_DBG if (info.nodeId == 0)
std::cout << "\tGoing through all "
<< allTuples.size()
<< " tuples in "
<< nNodes
<< " nodes\n";
// build container-n-d's
for (auto const& t: allTuples) {
// one which node(s) are the tuple elements located...
// put them into the right container
auto const _nodes = getTupleNodes(t, nNodes);
switch (_nodes.size()) {
case 1:
container1d[_nodes[0]].push_back(t);
break;
case 2:
container2d[ _nodes[0]
+ _nodes[1] * nNodes
].push_back(t);
break;
case 3:
container3d[ _nodes[0]
+ _nodes[1] * nNodes
+ _nodes[2] * nNodes * nNodes
].push_back(t);
break;
}
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 1-d containers\n";
// DISTRIBUTE 1-d containers
// every tuple which is only located at one node belongs to this node
{
auto const& _tuples = container1d[info.nodeId];
nodeTuples.resize(_tuples.size(), INVALID_TUPLE);
std::copy(_tuples.begin(), _tuples.end(), nodeTuples.begin());
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 2-d containers\n";
// DISTRIBUTE 2-d containers
//the tuples which are located at two nodes are half/half given to these nodes
for (size_t yx = 0; yx < container2d.size(); yx++) {
auto const& _tuples = container2d[yx];
const
size_t idx = yx % nNodes
// remeber: yx = idy * nNodes + idx
, idy = yx / nNodes
, n_half = _tuples.size() / 2
, size = nodeTuples.size()
;
size_t nbeg, nend;
if (info.nodeId == idx) {
nbeg = 0 * n_half;
nend = n_half;
} else if (info.nodeId == idy) {
nbeg = 1 * n_half;
nend = _tuples.size();
} else {
// either idx or idy is my node
continue;
}
size_t const nextra = nend - nbeg;
nodeTuples.resize(size + nextra, INVALID_TUPLE);
std::copy(_tuples.begin() + nbeg,
_tuples.begin() + nend,
nodeTuples.begin() + size);
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 3-d containers\n";
// DISTRIBUTE 3-d containers
for (size_t zyx = 0; zyx < container3d.size(); zyx++) {
auto const& _tuples = container3d[zyx];
const
size_t idx = zyx % nNodes
, idy = (zyx / nNodes) % nNodes
// remember: zyx = idx + idy * nNodes + idz * nNodes^2
, idz = zyx / nNodes / nNodes
, n_third = _tuples.size() / 3
, size = nodeTuples.size()
;
size_t nbeg, nend;
if (info.nodeId == idx) {
nbeg = 0 * n_third;
nend = 1 * n_third;
} else if (info.nodeId == idy) {
nbeg = 1 * n_third;
nend = 2 * n_third;
} else if (info.nodeId == idz) {
nbeg = 2 * n_third;
nend = _tuples.size();
} else {
// either idx or idy or idz is my node
continue;
}
size_t const nextra = nend - nbeg;
nodeTuples.resize(size + nextra, INVALID_TUPLE);
std::copy(_tuples.begin() + nbeg,
_tuples.begin() + nend,
nodeTuples.begin() + size);
}
WITH_DBG if (info.nodeId == 0) std::cout << "\tswapping tuples...\n";
/*
* sort part of group-and-sort algorithm
* every tuple on a given node is sorted in a way that
* the 'home elements' are the fastest index.
* 1:yyy 2:yyn(x) 3:yny(x) 4:ynn(x) 5:nyy 6:nyn(x) 7:nny 8:nnn
*/
for (auto &nt: nodeTuples){
if ( isOnNode(nt[0], nNodes) == info.nodeId ){ // 1234
if ( isOnNode(nt[2], nNodes) != info.nodeId ){ // 24
size_t const x(nt[0]);
nt[0] = nt[2]; // switch first and last
nt[2] = x;
}
else if ( isOnNode(nt[1], nNodes) != info.nodeId){ // 3
size_t const x(nt[0]);
nt[0] = nt[1]; // switch first two
nt[1] = x;
}
} else {
if ( isOnNode(nt[1], nNodes) == info.nodeId // 56
&& isOnNode(nt[2], nNodes) != info.nodeId
) { // 6
size_t const x(nt[1]);
nt[1] = nt[2]; // switch last two
nt[2] = x;
}
}
}
WITH_DBG if (info.nodeId == 0) std::cout << "\tsorting list of tuples...\n";
//now we sort the list of tuples
std::sort(nodeTuples.begin(), nodeTuples.end());
WITH_DBG if (info.nodeId == 0) std::cout << "\trestoring tuples...\n";
// we bring the tuples abc back in the order a<b<c
for (auto &t: nodeTuples) std::sort(t.begin(), t.end());
#if ATRIP_DEBUG > 1
WITH_DBG if (info.nodeId == 0)
std::cout << "checking for validity of " << nodeTuples.size() << std::endl;
const bool anyInvalid
= std::any_of(nodeTuples.begin(),
nodeTuples.end(),
[](ABCTuple const& t) { return t == INVALID_TUPLE; });
if (anyInvalid) throw "Some tuple is invalid in group-and-sort algorithm";
#endif
WITH_DBG if (info.nodeId == 0) std::cout << "\treturning tuples...\n";
return nodeTuples;
}
ABCTuples specialDistribution(Info const& info, ABCTuples const& allTuples);
// Distribution:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:1]]
std::vector<ABCTuple> main(MPI_Comm universe, size_t Nv) {
int rank, np;
MPI_Comm_rank(universe, &rank);
MPI_Comm_size(universe, &np);
std::vector<ABCTuple> result;
auto const nodeNames(getNodeNames(universe));
size_t const nNodes = unique(nodeNames).size();
auto const nodeInfos = getNodeInfos(nodeNames);
// We want to construct a communicator which only contains of one
// element per node
bool const computeDistribution
= nodeInfos[rank].localRank == 0;
std::vector<ABCTuple>
nodeTuples
= computeDistribution
? specialDistribution(Info{nNodes, nodeInfos[rank].nodeId},
getAllTuplesList(Nv))
: std::vector<ABCTuple>()
;
LOG(1,"Atrip") << "got nodeTuples\n";
// now we have to send the data from **one** rank on each node
// to all others ranks of this node
const
int color = nodeInfos[rank].nodeId
, key = nodeInfos[rank].localRank
;
MPI_Comm INTRA_COMM;
MPI_Comm_split(universe, color, key, &INTRA_COMM);
// Main:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:2]]
size_t const
tuplesPerRankLocal
= nodeTuples.size() / nodeInfos[rank].ranksPerNode
+ size_t(nodeTuples.size() % nodeInfos[rank].ranksPerNode != 0)
;
size_t tuplesPerRankGlobal;
MPI_Reduce(&tuplesPerRankLocal,
&tuplesPerRankGlobal,
1,
MPI_UINT64_T,
MPI_MAX,
0,
universe);
MPI_Bcast(&tuplesPerRankGlobal,
1,
MPI_UINT64_T,
0,
universe);
LOG(1,"Atrip") << "Tuples per rank: " << tuplesPerRankGlobal << "\n";
LOG(1,"Atrip") << "ranks per node " << nodeInfos[rank].ranksPerNode << "\n";
LOG(1,"Atrip") << "#nodes " << nNodes << "\n";
// Main:2 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:3]]
size_t const totalTuples
= tuplesPerRankGlobal * nodeInfos[rank].ranksPerNode;
if (computeDistribution) {
// pad with FAKE_TUPLEs
nodeTuples.insert(nodeTuples.end(),
totalTuples - nodeTuples.size(),
FAKE_TUPLE);
}
// Main:3 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:4]]
{
// construct mpi type for abctuple
MPI_Datatype MPI_ABCTUPLE;
MPI_Type_vector(nodeTuples[0].size(), 1, 1, MPI_UINT64_T, &MPI_ABCTUPLE);
MPI_Type_commit(&MPI_ABCTUPLE);
LOG(1,"Atrip") << "scattering tuples \n";
result.resize(tuplesPerRankGlobal);
MPI_Scatter(nodeTuples.data(),
tuplesPerRankGlobal,
MPI_ABCTUPLE,
result.data(),
tuplesPerRankGlobal,
MPI_ABCTUPLE,
0,
INTRA_COMM);
MPI_Type_free(&MPI_ABCTUPLE);
}
// Main:4 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:5]]
return result;
}
std::vector<ABCTuple> main(MPI_Comm universe, size_t Nv);
// Main:5 ends here
// [[file:~/cuda/atrip/atrip.org::*Interface][Interface:1]]
struct Distribution : public TuplesDistribution {
ABCTuples getTuples(size_t Nv, MPI_Comm universe) override {
return main(universe, Nv);
}
ABCTuples getTuples(size_t Nv, MPI_Comm universe) override;
};
// Interface:1 ends here

464
src/atrip/Tuples.cxx Normal file
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@ -0,0 +1,464 @@
#include <atrip/Tuples.hpp>
#include <atrip/Atrip.hpp>
namespace atrip {
template <typename A>
static A unique(A const &xs) {
auto result = xs;
std::sort(std::begin(result), std::end(result));
auto const& last = std::unique(std::begin(result), std::end(result));
result.erase(last, std::end(result));
return result;
}
std::vector<std::string> getNodeNames(MPI_Comm comm){
int rank, np;
MPI_Comm_rank(comm, &rank);
MPI_Comm_size(comm, &np);
std::vector<std::string> nodeList(np);
char nodeName[MPI_MAX_PROCESSOR_NAME];
char *nodeNames = (char*)malloc(np * MPI_MAX_PROCESSOR_NAME);
std::vector<int> nameLengths(np)
, off(np)
;
int nameLength;
MPI_Get_processor_name(nodeName, &nameLength);
MPI_Allgather(&nameLength,
1,
MPI_INT,
nameLengths.data(),
1,
MPI_INT,
comm);
for (int i(1); i < np; i++)
off[i] = off[i-1] + nameLengths[i-1];
MPI_Allgatherv(nodeName,
nameLengths[rank],
MPI_BYTE,
nodeNames,
nameLengths.data(),
off.data(),
MPI_BYTE,
comm);
for (int i(0); i < np; i++) {
std::string const s(&nodeNames[off[i]], nameLengths[i]);
nodeList[i] = s;
}
std::free(nodeNames);
return nodeList;
}
std::vector<RankInfo>
getNodeInfos(std::vector<string> const& nodeNames) {
std::vector<RankInfo> result;
auto const uniqueNames = unique(nodeNames);
auto const index = [&uniqueNames](std::string const& s) {
auto const& it = std::find(uniqueNames.begin(), uniqueNames.end(), s);
return std::distance(uniqueNames.begin(), it);
};
std::vector<size_t> localRanks(uniqueNames.size(), 0);
size_t globalRank = 0;
for (auto const& name: nodeNames) {
const size_t nodeId = index(name);
result.push_back({name,
nodeId,
globalRank++,
localRanks[nodeId]++,
(size_t)
std::count(nodeNames.begin(),
nodeNames.end(),
name)
});
}
return result;
}
ClusterInfo
getClusterInfo(MPI_Comm comm) {
auto const names = getNodeNames(comm);
auto const rankInfos = getNodeInfos(names);
return ClusterInfo {
unique(names).size(),
names.size(),
rankInfos[0].ranksPerNode,
rankInfos
};
}
ABCTuples getTuplesList(size_t Nv, size_t rank, size_t np) {
const size_t
// total number of tuples for the problem
n = Nv * (Nv + 1) * (Nv + 2) / 6 - Nv
// all ranks should have the same number of tuples_per_rank
, tuples_per_rank = n / np + size_t(n % np != 0)
// start index for the global tuples list
, start = tuples_per_rank * rank
// end index for the global tuples list
, end = tuples_per_rank * (rank + 1)
;
LOG(1,"Atrip") << "tuples_per_rank = " << tuples_per_rank << "\n";
WITH_RANK << "start, end = " << start << ", " << end << "\n";
ABCTuples result(tuples_per_rank, FAKE_TUPLE);
for (size_t a(0), r(0), g(0); a < Nv; a++)
for (size_t b(a); b < Nv; b++)
for (size_t c(b); c < Nv; c++){
if ( a == b && b == c ) continue;
if ( start <= g && g < end) result[r++] = {a, b, c};
g++;
}
return result;
}
ABCTuples getAllTuplesList(const size_t Nv) {
const size_t n = Nv * (Nv + 1) * (Nv + 2) / 6 - Nv;
ABCTuples result(n);
for (size_t a(0), u(0); a < Nv; a++)
for (size_t b(a); b < Nv; b++)
for (size_t c(b); c < Nv; c++){
if ( a == b && b == c ) continue;
result[u++] = {a, b, c};
}
return result;
}
ABCTuples atrip::NaiveDistribution::getTuples(size_t Nv, MPI_Comm universe) {
int rank, np;
MPI_Comm_rank(universe, &rank);
MPI_Comm_size(universe, &np);
return getTuplesList(Nv, (size_t)rank, (size_t)np);
}
namespace group_and_sort {
inline
size_t isOnNode(size_t tuple, size_t nNodes) { return tuple % nNodes; }
std::vector<size_t> getTupleNodes(ABCTuple const& t, size_t nNodes) {
std::vector<size_t>
nTuple = { isOnNode(t[0], nNodes)
, isOnNode(t[1], nNodes)
, isOnNode(t[2], nNodes)
};
return unique(nTuple);
}
ABCTuples specialDistribution(Info const& info, ABCTuples const& allTuples) {
ABCTuples nodeTuples;
size_t const nNodes(info.nNodes);
std::vector<ABCTuples>
container1d(nNodes)
, container2d(nNodes * nNodes)
, container3d(nNodes * nNodes * nNodes)
;
WITH_DBG if (info.nodeId == 0)
std::cout << "\tGoing through all "
<< allTuples.size()
<< " tuples in "
<< nNodes
<< " nodes\n";
// build container-n-d's
for (auto const& t: allTuples) {
// one which node(s) are the tuple elements located...
// put them into the right container
auto const _nodes = getTupleNodes(t, nNodes);
switch (_nodes.size()) {
case 1:
container1d[_nodes[0]].push_back(t);
break;
case 2:
container2d[ _nodes[0]
+ _nodes[1] * nNodes
].push_back(t);
break;
case 3:
container3d[ _nodes[0]
+ _nodes[1] * nNodes
+ _nodes[2] * nNodes * nNodes
].push_back(t);
break;
}
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 1-d containers\n";
// DISTRIBUTE 1-d containers
// every tuple which is only located at one node belongs to this node
{
auto const& _tuples = container1d[info.nodeId];
nodeTuples.resize(_tuples.size(), INVALID_TUPLE);
std::copy(_tuples.begin(), _tuples.end(), nodeTuples.begin());
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 2-d containers\n";
// DISTRIBUTE 2-d containers
//the tuples which are located at two nodes are half/half given to these nodes
for (size_t yx = 0; yx < container2d.size(); yx++) {
auto const& _tuples = container2d[yx];
const
size_t idx = yx % nNodes
// remeber: yx = idy * nNodes + idx
, idy = yx / nNodes
, n_half = _tuples.size() / 2
, size = nodeTuples.size()
;
size_t nbeg, nend;
if (info.nodeId == idx) {
nbeg = 0 * n_half;
nend = n_half;
} else if (info.nodeId == idy) {
nbeg = 1 * n_half;
nend = _tuples.size();
} else {
// either idx or idy is my node
continue;
}
size_t const nextra = nend - nbeg;
nodeTuples.resize(size + nextra, INVALID_TUPLE);
std::copy(_tuples.begin() + nbeg,
_tuples.begin() + nend,
nodeTuples.begin() + size);
}
WITH_DBG if (info.nodeId == 0)
std::cout << "\tBuilding 3-d containers\n";
// DISTRIBUTE 3-d containers
for (size_t zyx = 0; zyx < container3d.size(); zyx++) {
auto const& _tuples = container3d[zyx];
const
size_t idx = zyx % nNodes
, idy = (zyx / nNodes) % nNodes
// remember: zyx = idx + idy * nNodes + idz * nNodes^2
, idz = zyx / nNodes / nNodes
, n_third = _tuples.size() / 3
, size = nodeTuples.size()
;
size_t nbeg, nend;
if (info.nodeId == idx) {
nbeg = 0 * n_third;
nend = 1 * n_third;
} else if (info.nodeId == idy) {
nbeg = 1 * n_third;
nend = 2 * n_third;
} else if (info.nodeId == idz) {
nbeg = 2 * n_third;
nend = _tuples.size();
} else {
// either idx or idy or idz is my node
continue;
}
size_t const nextra = nend - nbeg;
nodeTuples.resize(size + nextra, INVALID_TUPLE);
std::copy(_tuples.begin() + nbeg,
_tuples.begin() + nend,
nodeTuples.begin() + size);
}
WITH_DBG if (info.nodeId == 0) std::cout << "\tswapping tuples...\n";
/*
* sort part of group-and-sort algorithm
* every tuple on a given node is sorted in a way that
* the 'home elements' are the fastest index.
* 1:yyy 2:yyn(x) 3:yny(x) 4:ynn(x) 5:nyy 6:nyn(x) 7:nny 8:nnn
*/
for (auto &nt: nodeTuples){
if ( isOnNode(nt[0], nNodes) == info.nodeId ){ // 1234
if ( isOnNode(nt[2], nNodes) != info.nodeId ){ // 24
size_t const x(nt[0]);
nt[0] = nt[2]; // switch first and last
nt[2] = x;
}
else if ( isOnNode(nt[1], nNodes) != info.nodeId){ // 3
size_t const x(nt[0]);
nt[0] = nt[1]; // switch first two
nt[1] = x;
}
} else {
if ( isOnNode(nt[1], nNodes) == info.nodeId // 56
&& isOnNode(nt[2], nNodes) != info.nodeId
) { // 6
size_t const x(nt[1]);
nt[1] = nt[2]; // switch last two
nt[2] = x;
}
}
}
WITH_DBG if (info.nodeId == 0) std::cout << "\tsorting list of tuples...\n";
//now we sort the list of tuples
std::sort(nodeTuples.begin(), nodeTuples.end());
WITH_DBG if (info.nodeId == 0) std::cout << "\trestoring tuples...\n";
// we bring the tuples abc back in the order a<b<c
for (auto &t: nodeTuples) std::sort(t.begin(), t.end());
#if ATRIP_DEBUG > 1
WITH_DBG if (info.nodeId == 0)
std::cout << "checking for validity of " << nodeTuples.size() << std::endl;
const bool anyInvalid
= std::any_of(nodeTuples.begin(),
nodeTuples.end(),
[](ABCTuple const& t) { return t == INVALID_TUPLE; });
if (anyInvalid) throw "Some tuple is invalid in group-and-sort algorithm";
#endif
WITH_DBG if (info.nodeId == 0) std::cout << "\treturning tuples...\n";
return nodeTuples;
}
std::vector<ABCTuple> main(MPI_Comm universe, size_t Nv) {
int rank, np;
MPI_Comm_rank(universe, &rank);
MPI_Comm_size(universe, &np);
std::vector<ABCTuple> result;
auto const nodeNames(getNodeNames(universe));
size_t const nNodes = unique(nodeNames).size();
auto const nodeInfos = getNodeInfos(nodeNames);
// We want to construct a communicator which only contains of one
// element per node
bool const computeDistribution
= nodeInfos[rank].localRank == 0;
std::vector<ABCTuple>
nodeTuples
= computeDistribution
? specialDistribution(Info{nNodes, nodeInfos[rank].nodeId},
getAllTuplesList(Nv))
: std::vector<ABCTuple>()
;
LOG(1,"Atrip") << "got nodeTuples\n";
// now we have to send the data from **one** rank on each node
// to all others ranks of this node
const
int color = nodeInfos[rank].nodeId,
key = nodeInfos[rank].localRank
;
MPI_Comm INTRA_COMM;
MPI_Comm_split(universe, color, key, &INTRA_COMM);
// Main:1 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:2]]
size_t const
tuplesPerRankLocal
= nodeTuples.size() / nodeInfos[rank].ranksPerNode
+ size_t(nodeTuples.size() % nodeInfos[rank].ranksPerNode != 0)
;
size_t tuplesPerRankGlobal;
MPI_Reduce(&tuplesPerRankLocal,
&tuplesPerRankGlobal,
1,
MPI_UINT64_T,
MPI_MAX,
0,
universe);
MPI_Bcast(&tuplesPerRankGlobal,
1,
MPI_UINT64_T,
0,
universe);
LOG(1,"Atrip") << "Tuples per rank: " << tuplesPerRankGlobal << "\n";
LOG(1,"Atrip") << "ranks per node " << nodeInfos[rank].ranksPerNode << "\n";
LOG(1,"Atrip") << "#nodes " << nNodes << "\n";
// Main:2 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:3]]
size_t const totalTuples
= tuplesPerRankGlobal * nodeInfos[rank].ranksPerNode;
if (computeDistribution) {
// pad with FAKE_TUPLEs
nodeTuples.insert(nodeTuples.end(),
totalTuples - nodeTuples.size(),
FAKE_TUPLE);
}
// Main:3 ends here
// [[file:~/cuda/atrip/atrip.org::*Main][Main:4]]
{
// construct mpi type for abctuple
MPI_Datatype MPI_ABCTUPLE;
MPI_Type_vector(nodeTuples[0].size(), 1, 1, MPI_UINT64_T, &MPI_ABCTUPLE);
MPI_Type_commit(&MPI_ABCTUPLE);
LOG(1,"Atrip") << "scattering tuples \n";
result.resize(tuplesPerRankGlobal);
MPI_Scatter(nodeTuples.data(),
tuplesPerRankGlobal,
MPI_ABCTUPLE,
result.data(),
tuplesPerRankGlobal,
MPI_ABCTUPLE,
0,
INTRA_COMM);
MPI_Type_free(&MPI_ABCTUPLE);
}
return result;
}
ABCTuples Distribution::getTuples(size_t Nv, MPI_Comm universe) {
return main(universe, Nv);
}
} // namespace group_and_sort
} // namespace atrip