diff --git a/src/Makefile b/src/Makefile
index cb3cdf2b1c47c34c7a3f8bae8ad35b4d2116399b..d9a4393e3c0d2d4a07e46d7a026a44f62dda19ed 100644
--- a/src/Makefile
+++ b/src/Makefile
@@ -26,10 +26,10 @@ LDOPT = -lginac $(TAULIB)
MPIEXEC = mpiexec
NP = 5
-MPISRC = masterworker.cpp mw_addslave.cpp \
+MPISRC = masterworker.cpp mw_addslave.cpp hierarchical.cpp \
perf.cpp sequential.cpp tensormatrix_mpi.cpp \
utils.cpp utils_parall.cpp profiling.cpp mw_combined.cpp
-# hierarchical.cpp
+
MPIOBJ= $(MPISRC:.cpp=.o)
diff --git a/src/hierarchical.cpp b/src/hierarchical.cpp
index ed447ccab0b12a862f5462ac99e7a8e2e00a9c92..87168ffc7e0e8bdaedd12b529563d433a3677d58 100644
--- a/src/hierarchical.cpp
+++ b/src/hierarchical.cpp
@@ -61,12 +61,16 @@ void create_communicators_hierarch( MPI_Comm& COMM_FOREMEN, MPI_Comm& COMM_TEAM
}
-gi::ex multiply_1level_foreman_hierarch_distribute_work( tensor3D_t& T, matrix_int_t& J, int size, parameters_t params, gi::lst symbols, MPI_Comm comm_team, int rank_foreman /* DEBUG */ ) {
+/*******************************************************************************
+ * Foreman *
+ *******************************************************************************/
+
+gi::ex multiply_2levels_foreman_hierarch_distribute_work( tensor3D_t& T, int size, parameters_2_1_t params, gi::lst symbols, MPI_Comm comm_team, int rank_foreman /* DEBUG */ ) {
gi::ex Tens = 0;
- gi::ex A;
- int a1, a2, a3, b1, b2, b3, c1, c2;
-
+ int a1, a2, a4, a6;
+ int N = size / 2;
+
MPI_Status status;
int unsigned len;
char* expr_c;
@@ -78,28 +82,21 @@ gi::ex multiply_1level_foreman_hierarch_distribute_work( tensor3D_t& T, matrix_i
/* Compute the points that need to be computed */
- A = gi::symbol( params.A );
- a1 = params.a1;
a2 = params.a2;
- a3 = params.a3;
- b1 = params.b1;
+ a4 = params.a4;
- std::vector<parameters_2_t> input;
+ std::vector<parameters_2_2_t> input;
std::vector<gi::ex> results;
- for( b2 = 0 ; b2 < size ; b2++ ) {
- for( b3 = 0 ; b3 < size ; b3++ ) {
- for( c1 = 0 ; c1 < size ; c1++ ) {
- for( c2 = 0 ; c2 < size ; c2++ ) {
- parameters_2_t p( A, a1, a2, a3, b1, b2, b3, c1, c2 );
- input.push_back( p );
- }
- }
+ for( a6 = 0 ; a6 < N ; a6++ ) {
+ for( a1 = 0 ; a1 < N ; a1++ ) {
+ parameters_2_2_t p( a4, a2, a1, a6 );
+ input.push_back( p );
}
}
/* Distribute the work */
- /* Very copy/paste from multiply_1level_master -> possible refactoring here */
+ /* Very copy/paste from multiply_2levels_master -> possible refactoring here */
while( input.size() > 0 ) {
MPI_Recv( &len, 1, MPI_UNSIGNED, MPI_ANY_SOURCE, MPI_ANY_TAG, comm_team, &status );
@@ -182,7 +179,7 @@ gi::ex multiply_1level_foreman_hierarch_distribute_work( tensor3D_t& T, matrix_i
return Tens;
}
-void multiply_1level_foreman_hierarch_finalize( MPI_Comm comm_team ) {
+void multiply_2levels_foreman_hierarch_finalize( MPI_Comm comm_team ) {
int src, np, running = 0;
unsigned int len;
@@ -200,13 +197,13 @@ void multiply_1level_foreman_hierarch_finalize( MPI_Comm comm_team ) {
return;
}
-void multiply_1level_foreman_hierarch( tensor3D_t& T, matrix_int_t& J, int size, MPI_Comm comm_foremen, MPI_Comm comm_team ) {
+void multiply_2levels_foreman_hierarch( tensor3D_t& T, int size, MPI_Comm comm_foremen, MPI_Comm comm_team ) {
gi::ex Tens;
gi::lst symbols;
unsigned int len = 0;
- parameters_t params;
+ parameters_2_1_t params;
MPI_Status status;
char* expr_c;
@@ -224,25 +221,25 @@ void multiply_1level_foreman_hierarch( tensor3D_t& T, matrix_int_t& J, int size,
while( true ){
/* Receive a set of parameters */
-
- MPI_Recv( ¶ms, 1, DT_PARAMETERS, ROOT, MPI_ANY_TAG, comm_foremen, &status );
-
+
+ MPI_Recv( ¶ms, 1, DT_PARAMETERS_2_1, ROOT, MPI_ANY_TAG, comm_foremen, &status );
+
if( status.MPI_TAG == TAG_WORK ){
/* Distribute the work on my workers */
- Tens = multiply_1level_foreman_hierarch_distribute_work( T, J, size, params, symbols, comm_team, rank /* DEBUG */ );
+ Tens = multiply_2levels_foreman_hierarch_distribute_work( T, size, params, symbols, comm_team, rank /* DEBUG */ );
- /* Send the result to the master */
+ /* Send the result to the master */
- send_result( Tens, comm_foremen);
+ send_result( Tens, comm_foremen );
} else {
if( status.MPI_TAG == TAG_END ){
-
+
/* The end: forward the signal to our workers */
- multiply_1level_foreman_hierarch_finalize( comm_team );
+ multiply_2levels_foreman_hierarch_finalize( comm_team );
return;
} else {
std::cerr << "Wrong tag received on slave " << status.MPI_TAG << std::endl;
@@ -251,13 +248,17 @@ void multiply_1level_foreman_hierarch( tensor3D_t& T, matrix_int_t& J, int size,
}
}
-void multiply_1level_slave_hierarch( tensor3D_t& T, matrix_int_t& J, int size, MPI_Comm comm ) {
+/*******************************************************************************
+ * Worker *
+ *******************************************************************************/
+
+void multiply_2levels_slave_hierarch( tensor3D_t& T, int size, MPI_Comm comm ) {
gi::ex Tens;
- int a1, a2, a3, b1, b2, b3, c1, c2;
+ int a1, a2, a4, a6;
unsigned int len = 0;
- parameters_2_t params;
+ parameters_2_2_t params;
MPI_Status status;
char* expr_c;
@@ -272,21 +273,16 @@ void multiply_1level_slave_hierarch( tensor3D_t& T, matrix_int_t& J, int size, M
while( true ){
/* Receive a set of parameters */
- MPI_Recv( ¶ms, 1, DT_PARAMETERS_2, ROOT, MPI_ANY_TAG, comm, &status );
+ MPI_Recv( ¶ms, 1, DT_PARAMETERS_2_2, ROOT, MPI_ANY_TAG, comm, &status );
+
if( status.MPI_TAG == TAG_WORK ){
- a1 = params.a1;
+ a4 = params.a4;
a2 = params.a2;
- a3 = params.a3;
- b1 = params.b1;
- b2 = params.b2;
- b3 = params.b3;
- c1 = params.c1;
- c2 = params.c2;
-
- gi::symbol A( std::string( params.A ) );
-
- Tens = one_level2_product( &T, &J, A, size, a1, a2, a3, b1, b2, b3, c1, c2 );
+ a1 = params.a1;
+ a6 = params.a6;
+
+ Tens = two_level2_product( &T, size, a4, a2, a1, a6 );
if( Tens.is_zero() ) {
len = 0;
@@ -324,6 +320,152 @@ void multiply_1level_slave_hierarch( tensor3D_t& T, matrix_int_t& J, int size, M
}
+/*******************************************************************************
+ * Master *
+ *******************************************************************************/
+
+gi::ex multiply_2levels_master( tensor3D_t& T, unsigned int size, MPI_Comm comm = MPI_COMM_WORLD ) {
+ gi::ex Tens = 0;
+ unsigned int a2, a4;
+ gi::lst symbols;
+
+ MPI_Status status;
+ char* expr_c;
+ size_t expr_c_size = 0;
+ int src, np, running = 0;
+ unsigned int len;
+ parameters_2_1_t pzero( 0, 0 );
+
+ MPI_Comm_size( comm, &np );
+
+ expr_c = NULL;
+ expr_c = (char*) malloc( 3279 ); // TMP
+
+ int i, j;
+ i = 0;
+ j = 0;
+
+ int receivedresults = 0;
+ unsigned int N = size/2;
+
+ std::vector<parameters_2_1_t> input;
+ std::vector<std::string> results_s;
+ std::vector<gi::ex> results;
+
+ /* Build a list of argument sets */
+
+ for( a4 = 0 ; a4 < N ; a4++ ){
+ for( a2 = 0; a2 < N ; a2++ ){
+ parameters_2_1_t p( a4, a2 );
+ input.push_back( p );
+ }
+ }
+
+ /* Compute the set of symbols */
+ /* Could be done while the first slave is working */
+
+ symbols = all_symbols_3D( size );
+
+ /* Distribute the work */
+
+ while( input.size() > 0 ) {
+ MPI_Recv( &len, 1, MPI_UNSIGNED, MPI_ANY_SOURCE, MPI_ANY_TAG, comm, &status );
+ src = status.MPI_SOURCE;
+
+ if( status.MPI_TAG == TAG_PULL ) {
+
+ /* Nothing else will come: just send wome work */
+ send_work( input, src, comm );
+ running++;
+
+ } else {
+ if( status.MPI_TAG == TAG_RES ){
+ src = status.MPI_SOURCE;
+
+ /* The first message contains the length of what is coming next */
+ if( len != 0 ) {
+ if( len > expr_c_size ) {
+ expr_c_size = len;
+ if( NULL != expr_c ) free( expr_c );
+ expr_c = (char*)malloc( expr_c_size ); // The \0 was added by the slave
+ }
+
+ /* Receive the result */
+ MPI_Recv( expr_c, len, MPI_CHAR, src, TAG_EXPR, comm, &status );
+
+ /* put it in the result queue */
+ std::string s( expr_c );
+
+ send_work( input, src, comm );
+
+ /* Process what I have just received */
+ /* Could be given to a slave... */
+ gi::ex received = de_linearize_expression( s, symbols );
+ Tens += received;
+#if DEBUG
+ results.push_back( received );
+ results_s.push_back( s );
+ receivedresults++;
+#endif
+ } else {
+ /* Send more work */
+ send_work( input, src, comm );
+ }
+ } else{
+ std::cerr << "Wrong tag received " << status.MPI_TAG << std::endl;
+ }
+ }
+ }
+
+ /* Wait until everyone is done */
+
+ // running = np - 1; // all the foremen are running
+ while( running > 0 ) {
+
+ MPI_Recv( &len, 1, MPI_UNSIGNED, MPI_ANY_SOURCE, MPI_ANY_TAG, comm, &status );
+ src = status.MPI_SOURCE;
+
+ if( len != 0 ) {
+ if( len > expr_c_size ) {
+ expr_c_size = len;
+ if( NULL != expr_c ) free( expr_c );
+ expr_c = (char*)malloc( expr_c_size ); // The \0 was added by the slave
+ }
+
+ /* Receive the result */
+ MPI_Recv( expr_c, len, MPI_CHAR, src, TAG_EXPR, comm, &status );
+
+ /* And send the END signal */
+ send_end( src, pzero, comm );
+ running--;
+
+ /* Process what I have just received */
+ /* Could be given to a slave... */
+ /* put it in the result queue */
+ std::string s( expr_c );
+ gi::ex received = de_linearize_expression( s, symbols );
+ Tens += received;
+#if DEBUG
+ results.push_back( received );
+ results_s.push_back( s );
+ receivedresults++;
+#endif
+ } else {
+ send_end( src, comm );
+ running--;
+ }
+ }
+
+#if DEBUG
+ std::cout << "Received " << receivedresults << " results" << std::endl;
+
+ std::cout << "Tpara=" << Tens << ";" << std::endl;
+#endif
+
+ if( NULL != expr_c) free( expr_c );
+ return Tens;
+}
+
/* The master sends a parameter set to a foreman.
The foreman computes a set of parameter sets and distributes them to the workers.
The foreman adds the results and, when everything is done, sends the total to the master.
@@ -338,7 +480,7 @@ void multiply_1level_slave_hierarch( tensor3D_t& T, matrix_int_t& J, int size, M
F -> M: Same
*/
-gi::ex multiply_1level_mw_hierarch( tensor3D_t& T, matrix_int_t& J, int size ) { // simpler: same dimension everywhere
+gi::ex multiply_2levels_mw_hierarch( tensor3D_t& T, int size ) { // simpler: same dimension everywhere
int rank;
gi::ex Tens = 0;
MPI_Comm COMM_FOREMEN, COMM_TEAM;
@@ -370,14 +512,14 @@ gi::ex multiply_1level_mw_hierarch( tensor3D_t& T, matrix_int_t& J, int size ) {
/* Here we go*/
if( 0 == rank ) {
- Tens = multiply_1level_master( T, J, size, COMM_FOREMEN );
+ Tens = multiply_2levels_master( T, size, COMM_FOREMEN );
} else {
int rank_foreman;
MPI_Comm_rank( COMM_TEAM, &rank_foreman );
if( 0 == rank_foreman ) {
- multiply_1level_foreman_hierarch( T, J, size, COMM_FOREMEN, COMM_TEAM );
+ multiply_2levels_foreman_hierarch( T, size, COMM_FOREMEN, COMM_TEAM );
} else {
- multiply_1level_slave_hierarch( T, J, size, COMM_TEAM );
+ multiply_2levels_slave_hierarch( T, size, COMM_TEAM );
}
}
diff --git a/src/tensormatrix.cpp b/src/tensormatrix.cpp
index 77fdc2bf5df1bcb7a640b00821f8846c12eeefd3..eeba3e67a4e2fb28fb7e3a98c7ae146cf1202dc5 100644
--- a/src/tensormatrix.cpp
+++ b/src/tensormatrix.cpp
@@ -1,7 +1,6 @@
#include <iostream>
#include <cstdlib>
#include <ginac/ginac.h>
-//#include <starpu.h>
#define N 4
@@ -18,7 +17,7 @@ typedef std::vector<int> vector_int_t;
/*
libginac-dev ginac-tools
- g++ -O3 -Wall -o tensormatrix tensormatrix.cpp -lginac
+ g++ -std=c++11 -O3 -Wall -o tensormatrix tensormatrix.cpp -lginac
*/
/* Sequentiel sur Minimum
real 3m31,034s
diff --git a/src/tensormatrix.h b/src/tensormatrix.h
index a21dca21e0d20aa55e93ab8e2fde7c34a2fd49c5..dd936bfd53c439327a22d0adff267281484c6a9f 100644
--- a/src/tensormatrix.h
+++ b/src/tensormatrix.h
@@ -25,7 +25,7 @@ gi::ex multiply_2levels( tensor3D_t&, int );
// parallel
gi::ex multiply_1level_mw( tensor3D_t&, int );
gi::ex multiply_1level_mw_addslave( tensor3D_t&, int );
-gi::ex multiply_1level_mw_hierarch( tensor3D_t&, matrix_int_t&, int );
+gi::ex multiply_2levels_mw_hierarch( tensor3D_t&, int );
gi::ex multiply_combined( tensor3D_t&, int );
/*******************************************************************************
diff --git a/src/tensormatrix_mpi.cpp b/src/tensormatrix_mpi.cpp
index 39a89de53e3dd0a15bc11cc1341d0c9fe270a067..9b42408df4429210ae39695fb15e936556e79945 100644
--- a/src/tensormatrix_mpi.cpp
+++ b/src/tensormatrix_mpi.cpp
@@ -114,7 +114,7 @@ int main( int argc, char** argv ){
break;
}
if( argc >= 4 ) {
- nbforemen = atoi( argv[3] ); /* these two variables are obtained from the same CI parameter but since they are */
+ nbforemen = atoi( argv[3] ); /* these two variables are obtained from the same CLI parameter but since they are */
maxresult = atoi( argv[3] ); /* used in two functions for two purposes, use two different names */
}
}
@@ -138,9 +138,9 @@ int main( int argc, char** argv ){
case 'a':
Tpara = multiply_1level_mw_addslave( T, N );
break;
- /*case 'h':
- Tpara = multiply_1level_mw_hierarch( T, J, N );
- break;*/
+ case 'h':
+ Tpara = multiply_2levels_mw_hierarch( T, N );
+ break;
case 'c':
Tpara = multiply_combined( T, N );
break;
diff --git a/src/utils_parall.cpp b/src/utils_parall.cpp
index 64c7beccccb51340839383a80d5cbf99f2015be7..3ce59790315815f7455f2601b32f1519ca5c8d26 100644
--- a/src/utils_parall.cpp
+++ b/src/utils_parall.cpp
@@ -31,9 +31,11 @@ parameters_2_1_t::parameters_2_1_t( unsigned int a4, unsigned int a2 ){
this->a2 = a2;
}
-parameters_2_2_t::parameters_2_2_t( unsigned int a4, unsigned int a2 ){
- this->a6 = a6;
+parameters_2_2_t::parameters_2_2_t( unsigned int a4, unsigned int a2, unsigned int a1, unsigned int a6 ){
+ this->a4 = a4;
+ this->a2 = a2;
this->a1 = a1;
+ this->a6 = a6;
}
void create_parameters_datatye(){
@@ -46,8 +48,8 @@ void create_parameters_datatye_2_1(){
MPI_Type_commit( &DT_PARAMETERS_2_1 );
}
-void create_parameters_datatye_2(){
- MPI_Type_contiguous( 2, MPI_UNSIGNED, &DT_PARAMETERS_2_2 );
+void create_parameters_datatye_2_2(){
+ MPI_Type_contiguous( 4, MPI_UNSIGNED, &DT_PARAMETERS_2_2 );
MPI_Type_commit( &DT_PARAMETERS_2_2 );
}
@@ -79,6 +81,11 @@ void send_end( int peer, MPI_Comm comm ) {
MPI_Send( ¶, 1, DT_PARAMETERS, peer, TAG_END, comm );
}
+void send_end( int peer, parameters_2_1_t p, MPI_Comm comm ) {
+ /* The parameters_2_1_t argument is not used, but needed to instinguish between functions */
+ MPI_Send( &p, 1, DT_PARAMETERS_2_1, peer, TAG_END, comm );
+}
+
void send_end_batch( int peer, MPI_Comm comm ) {
parameters_t para;
MPI_Send( ¶, 1, DT_PARAMETERS_2_1, peer, TAG_END_BATCH, comm );
@@ -98,6 +105,12 @@ void send_work( std::vector<parameters_2_1_t>& input, int peer, MPI_Comm comm ){
MPI_Send( ¶, 1, DT_PARAMETERS_2_1, peer, TAG_WORK, comm );
}
+void send_work( std::vector<parameters_2_2_t>& input, int peer, MPI_Comm comm ){
+ parameters_2_2_t para = input.back();
+ input.pop_back();
+ MPI_Send( ¶, 1, DT_PARAMETERS_2_2, peer, TAG_WORK, comm );
+}
+
/* M -> W: Send a set of expressions to be added */
void send_expressions_to_add( std::vector<std::string>& results, int peer ) {
diff --git a/src/utils_parall.h b/src/utils_parall.h
index bf9ebb22cd28e85d744d53c5241e45fe6237ad3e..a0083e88a1e7e5684c8f98a74a9fbb17fb030cea 100644
--- a/src/utils_parall.h
+++ b/src/utils_parall.h
@@ -21,10 +21,11 @@ public:
parameters_2_1_t( unsigned int, unsigned int );
parameters_2_1_t( void ){};
};
+
class parameters_2_2_t{
public:
- unsigned int a6, a1;
- parameters_2_2_t( unsigned int, unsigned int );
+ unsigned int a4, a2, a6, a1;
+ parameters_2_2_t( unsigned int, unsigned int, unsigned int, unsigned int );
parameters_2_2_t( void ){};
};
@@ -38,12 +39,14 @@ gi::ex de_linearize_expression( std::string, gi::lst );
void send_work( std::vector<parameters_t>& input, int peer, MPI_Comm comm = MPI_COMM_WORLD );
void send_work( std::vector<parameters_2_2_t>& input, int peer, MPI_Comm comm = MPI_COMM_WORLD );
+void send_work( std::vector<parameters_2_1_t>& input, int peer, MPI_Comm comm );
void send_expressions_to_add( std::vector<std::string>&, int );
void send_add_or_end_addslave( std::vector<std::string>&, int, int* );
void send_work_addslave( std::vector<parameters_t>&, std::vector<std::string>&, int ) ;
void send_result( gi::ex T, MPI_Comm comm = MPI_COMM_WORLD );
void send_end( int peer, MPI_Comm comm = MPI_COMM_WORLD );
+void send_end( int peer, parameters_2_1_t p, MPI_Comm comm = MPI_COMM_WORLD );
void send_end_batch( int peer, MPI_Comm comm = MPI_COMM_WORLD );
void create_parameters_datatye( void );