diff --git a/src/Makefile b/src/Makefile
index a1f518d3b8fbc38920ad4e383d96472541c02192..a257ab72d62caa572f734ec4c7967c3ed22170f8 100644
--- a/src/Makefile
+++ b/src/Makefile
@@ -29,7 +29,8 @@ NP = 5
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 \
- masterworker2.cpp mw_addslave2.cpp hierarchical2.cpp
+ masterworker2.cpp mw_addslave2.cpp hierarchical2.cpp \
+ masterworker3.cpp
MPIOBJ= $(MPISRC:.cpp=.o)
diff --git a/src/products.h b/src/products.h
index 1c6bc3ad5ed7c4a8ed6c0495ce69401916346712..932876255010c44c4c4bc961ca8ff62bd9284c0c 100644
--- a/src/products.h
+++ b/src/products.h
@@ -8,6 +8,7 @@ namespace gi = GiNaC;
// internal (sequential) routines
gi::ex one_level1_product( tensor3D_t*, int, int, int, int );
+gi::ex one_level1_product( tensor3D_t*, int, int, int );
gi::ex one_level1_product( tensor3D_t*, int, int );
gi::ex one_level2_product( tensor3D_t*, int, int, int, int, int );
gi::ex two_level1_product( tensor3D_t*, int, int, int );
diff --git a/src/sequential.cpp b/src/sequential.cpp
index 11da914f02b9117b65878387e43eec28829a1d2a..0634853ff8bc76b49c97652abc5e01d58b3d2c44 100644
--- a/src/sequential.cpp
+++ b/src/sequential.cpp
@@ -341,6 +341,91 @@ gi::ex one_level1_product( tensor3D_t* T, int size, int a4 ){
return Tens;
}
+gi::ex one_level1_product( tensor3D_t* T, int size, int a4, int a2 ){
+
+ gi::ex Tens = 0;
+ gi::ex Ti0, Ti1, Ti2;
+ gi::ex W1, W2, W3, W4, W5, W6, W7;
+ gi::ex Z1, Z2, Z6, t5, tE, t1, t12, t123, t126, t13, t134, t14, t16, t2, t23, t24, t26, t3, t4, X7Y5;
+ gi::ex TE, T1, T2, T3, T4, T5, T12, T13, T14, T16, T23, T24, T26, T123, T126, T134;
+ const char timerB[] = "B";
+
+ int a1, a3, a5, a6;
+ int A1, A2, A3, A4, A5, A6;
+ TE = T1 = T2 = T3 = T4 = T5 = T12 = T13 = T14 = T16 = T23 = T24 = T26 = T123 = T126 = T134 = 0;
+ Ti0 = Ti1 = 0;
+
+ int N = size/2;
+
+ A4 = a4 + N;
+ A2 = a2 + N;
+ for( a6 = 0 ; a6 < N ; a6++ ) {
+ A6 = a6 + N;
+
+ W1 = (*T)[a4][a2][a6];
+ W2 = (*T)[a4][A2][a6];
+ W3 = (*T)[a4][a2][A6];
+ W4 = (*T)[A4][A2][a6];
+ W5 = (*T)[a4][A2][A6];
+ W6 = (*T)[A4][a2][A6];
+ W7 = (*T)[A4][A2][A6];
+
+ Ti1 = 0;
+ for( a1 = 0 ; a1 < N ; a1++ ) {
+ A1 = a1 + N;
+ Ti0 = TE = T12 = T13 = T14 = T16 = T23 = T24 = T26 = T1 = T2 = T3 = T4 = T5 = T123 = T126 = T134 = 0;
+ for( a5 = 0 ; a5 < N ; a5++ ) {
+ A5 = a5 + N;
+ Z1 = (*T)[a1][a5][a6];
+ Z2 = (*T)[A1][a5][a6];
+ Z6 = (*T)[A1][a5][A6];
+ t5 = W3*(*T)[a1][A5][a6];
+ tE = W4*(*T)[A1][A5][A6];
+ t1 = W3*Z2;
+ t13 = t1;
+ t2 = W5*Z1;
+ t23 = t2;
+ t3 = W3*Z1;
+ t4 = W6*Z1;
+ t12 = W5*Z2;
+ t14 = W6*Z2;
+ t134 = t14 ;
+ t16 = W1*Z6;
+ t24 = W7*Z1;
+ t26 = W2*(*T)[a1][a5][A6];
+ t123 = W5*Z2;
+ t126 = W2*Z6;
+
+ for( a3 = 0 ; a3 < N ; a3++ ) {
+ A3 = a3 + N;
+ TE = TE + tE*(*T)[a1][a2][a3]*(*T)[a4][a5][A3];
+ T5 = T5 + t5*(*T)[A1][A2][A3]*(*T)[A4][a5][a3];
+ X7Y5 = (*T)[a1][A2][A3]*(*T)[A4][A5][a3];
+ T1 = T1 + t1*X7Y5;
+ T16 = T16 + t16*X7Y5;
+ T2 = T2 + t2*(*T)[A1][a2][A3]*(*T)[A4][A5][a3];
+ T3 = T3 + t3*(*T)[A1][A2][a3]*(*T)[A4][A5][A3];
+ T4 = T4 + t4*(*T)[A1][A2][A3]*(*T)[a4][A5][a3];
+ T12 = T12 + t12*(*T)[a1][a2][A3]*(*T)[A4][A5][a3];
+ T13 = T13 + t13*(*T)[a1][A2][a3]*(*T)[A4][A5][A3];
+ T14 = T14 + t14*(*T)[a1][A2][A3]*(*T)[a4][A5][a3];
+ T23 = T23 + t23*(*T)[A1][a2][a3]*(*T)[A4][A5][A3];
+ T24 = T24 + t24*(*T)[A1][a2][A3]*(*T)[a4][A5][a3];
+ T26 = T26 + t26*(*T)[A1][a2][A3]*(*T)[A4][A5][a3];
+ T123 = T123 + t123*(*T)[a1][a2][a3]*(*T)[A4][A5][A3];
+ T126 = T126 + t126*(*T)[a1][a2][A3]*(*T)[A4][A5][a3];
+ T134 = T134 + t134*(*T)[a1][A2][a3]*(*T)[a4][A5][A3];
+ }
+ Ti0 += ( 4*(TE+T12+T13+T14+T16+T23+T24+T26 - (T1 + T2 + T3 + T4 + T5 +T123 + T126 + T134)) );
+ }
+ Ti1 += Ti0;
+ }
+ Tens += Ti1;
+ }
+
+ return Tens;
+}
+
gi::ex one_level2_product( tensor3D_t* T, int size, int a4, int a2, int a1, int a6 ){
int a3, a5;
diff --git a/src/tensormatrix.h b/src/tensormatrix.h
index 05bca94a3b19eac71ec31f3e346a9b76209ae1a2..cfb5fbc9298c3c3d445c2c10b8a6ca401e793a01 100644
--- a/src/tensormatrix.h
+++ b/src/tensormatrix.h
@@ -25,6 +25,7 @@ gi::ex multiply_2levels( tensor3D_t&, int );
// parallel
gi::ex multiply_1level_mw( tensor3D_t&, int );
gi::ex multiply_1level_mw2( tensor3D_t&, int );
+gi::ex multiply_1level_mw3( tensor3D_t&, int );
gi::ex multiply_1level_mw_addslave( tensor3D_t&, int );
gi::ex multiply_1level_mw_addslave2( tensor3D_t&, int );
gi::ex multiply_2levels_mw_hierarch( tensor3D_t&, int );
diff --git a/src/tensormatrix_mpi.cpp b/src/tensormatrix_mpi.cpp
index a0482ae69d22560ca255570e706210bd3d9d2717..279d24eb8010b4b0edc23b07abb2d53174b40b95 100644
--- a/src/tensormatrix_mpi.cpp
+++ b/src/tensormatrix_mpi.cpp
@@ -28,7 +28,8 @@ namespace gi = GiNaC;
tensormatrix_mpi [N] [Function name] [Nb of foremen]
Function names being:
- M/m: Master-Worker -> multiply_1level_mw
- - n/n: Master-Worker, coarser grain -> multiply_1level_mw2
+ - n/N: Master-Worker, coarser grain -> multiply_1level_mw2
+ - o/O: Master-Worker, middle grain -> multiply_1level_mw3
- A/a: Master-Worker, addition on a slave -> multiply_1level_mw_addslave
- B/b: Master-Worker, coarser grain, addition on a slave -> multiply_1level_mw_addslave2
- H/h: Hierarchical master-worker -> multiply_1level_mw_hierarch
@@ -97,6 +98,10 @@ int main( int argc, char** argv ){
case 'n':
tostart = 'n';
break;
+ case 'O':
+ case 'o':
+ tostart = 'o';
+ break;
case 'A':
case 'a':
tostart = 'a';
@@ -154,6 +159,9 @@ int main( int argc, char** argv ){
case 'n':
Tpara = multiply_1level_mw2( T, N );
break;
+ case 'o':
+ Tpara = multiply_1level_mw3( T, N );
+ break;
case 'a':
Tpara = multiply_1level_mw_addslave( T, N );
break;