.github/workflows/main.yml

@@ -2,8 +2,6 @@
 name: CI
 
 on:
-  push:
-    branches: [ master, cuda ]
   pull_request:
     branches: [ master, cuda ]
 

README.org

@@ -87,10 +87,7 @@ sed "s/^# //; s/^# *$//; /^$/d"
   and without computing slices.
 - only-dgemm ::
   This only runs the computation part that involves dgemms.
-- cuda-only-dgemm ::
+- slices-on-gpu-only-dgemm ::
-  This is the naive CUDA implementation compiling only the dgemm parts
-  of the compute.
-- cuda-slices-on-gpu-only-dgemm ::
   This configuration tests that slices reside completely on the gpu
   and it should use a CUDA aware MPI implementation.
   It also only uses the routines that involve dgemm.
@@ -117,13 +114,13 @@ Notice that you can give a path for ctf for all of them by doing
 
 ** Main benchmark
 
-The main benchmark gets built in =bench/atrip= and is used to run an
+The main benchmark gets built in =bench/main= and is used to run an
 atrip run with random tensors.
 
 A common run of this script will be the following
 
 #+begin_src sh
-bench/atrip \
+bench/main \
   --no 100 \
   --nv 1000 \
   --mod 1 \

bench/main.cxx

@@ -5,15 +5,13 @@
 #include <CLI11.hpp>
 
 #define _print_size(what, size)                 \
-  do {                                          \
   if (rank == 0) {                              \
     std::cout << #what                          \
               << " => "                         \
               << (double)size * elem_to_gb      \
               << "GB"                           \
               << std::endl;                     \
-    }                                           \
+  }
-  } while (0)
 
 int main(int argc, char** argv) {
   MPI_Init(&argc, &argv);
@@ -50,19 +48,6 @@ int main(int argc, char** argv) {
                  checkpoint_percentage,
                  "Percentage for checkpoints");
 
-  // Optional tensor files
-  std::string
-    ei_path, ea_path,
-    Tph_path, Tpphh_path,
-    Vpphh_path, Vhhhp_path, Vppph_path;
-  app.add_option("--ei", ei_path, "Path for ei");
-  app.add_option("--ea", ea_path, "Path for ea");
-  app.add_option("--Tpphh", Tpphh_path, "Path for Tpphh");
-  app.add_option("--Tph", Tph_path, "Path for Tph");
-  app.add_option("--Vpphh", Vpphh_path, "Path for Vpphh");
-  app.add_option("--Vhhhp", Vhhhp_path, "Path for Vhhhp");
-  app.add_option("--Vppph", Vppph_path, "Path for Vppph");
-
 #if defined(HAVE_CUDA)
   size_t ooo_threads = 0, ooo_blocks = 0;
   app.add_option("--ooo-blocks",
@@ -166,64 +151,37 @@ int main(int argc, char** argv) {
   }
 
 
-  std::vector<int>
+  std::vector<int> symmetries(4, NS)
-    symmetries(4, NS),
+                 , vo({nv, no})
-    vo({nv, no}),
+                 , vvoo({nv, nv, no, no})
-    vvoo({nv, nv, no, no}),
+                 , ooov({no, no, no, nv})
-    ooov({no, no, no, nv}),
+                 , vvvo({nv, nv, nv, no})
-    vvvo({nv, nv, nv, no});
+                 ;
 
   CTF::Tensor<double>
-    ei(1, ooov.data(), symmetries.data(), world),
+      ei(1, ooov.data(), symmetries.data(), world)
-    ea(1, vo.data(), symmetries.data(), world),
+    , ea(1, vo.data(), symmetries.data(), world)
-    Tph(2, vo.data(), symmetries.data(), world),
+    , Tph(2, vo.data(), symmetries.data(), world)
-    Tpphh(4, vvoo.data(), symmetries.data(), world),
+    , Tpphh(4, vvoo.data(), symmetries.data(), world)
-    Vpphh(4, vvoo.data(), symmetries.data(), world),
+    , Vpphh(4, vvoo.data(), symmetries.data(), world)
-    Vhhhp(4, ooov.data(), symmetries.data(), world);
+    , Vhhhp(4, ooov.data(), symmetries.data(), world)
+    ;
 
   // initialize deletable tensors in heap
   auto Vppph
     = new CTF::Tensor<double>(4, vvvo.data(), symmetries.data(), world);
 
-  _print_size(Vabci, no*nv*nv*nv);
+  _print_size(Vabci, no*nv*nv*nv)
-  _print_size(Vabij, no*no*nv*nv);
+  _print_size(Vabij, no*no*nv*nv)
-  _print_size(Vijka, no*no*no*nv);
+  _print_size(Vijka, no*no*no*nv)
 
-  if (ei_path.size()) {
-    ei.read_dense_from_file(ei_path.c_str());
-  } else {
   ei.fill_random(-40.0, -2);
-  }
-  if (ea_path.size()) {
-    ea.read_dense_from_file(ea_path.c_str());
-  } else {
   ea.fill_random(2, 50);
-  }
-  if (Tpphh_path.size()) {
-    Tpphh.read_dense_from_file(Tpphh_path.c_str());
-  } else {
   Tpphh.fill_random(0, 1);
-  }
-  if (Tph_path.size()) {
-    Tph.read_dense_from_file(Tph_path.c_str());
-  } else {
   Tph.fill_random(0, 1);
-  }
-  if (Vpphh_path.size()) {
-    Vpphh.read_dense_from_file(Vpphh_path.c_str());
-  } else {
   Vpphh.fill_random(0, 1);
-  }
-  if (Vhhhp_path.size()) {
-    Vhhhp.read_dense_from_file(Vhhhp_path.c_str());
-  } else {
   Vhhhp.fill_random(0, 1);
-  }
-  if (Vppph_path.size()) {
-    Vppph->read_dense_from_file(Vppph_path.c_str());
-  } else {
   Vppph->fill_random(0, 1);
-  }
 
   atrip::Atrip::init(MPI_COMM_WORLD);
   const auto in

etc/env/raven/cuda

@@ -1,56 +0,0 @@
-mods=(
-  cuda/11.6
-  intel/19.1.2
-  mkl/2020.4
-  impi/2019.8
-  autoconf/2.69
-  automake/1.15
-  libtool/2.4.6
-)
-
-
-module purge
-module load ${mods[@]}
-LIB_PATH="${CUDA_HOME}/lib64"
-export CUDA_ROOT=${CUDA_HOME}
-export CUDA_LDFLAGS="-L${LIB_PATH} -lcuda -L${LIB_PATH} -lcudart -L${LIB_PATH} -lcublas"
-export CUDA_CXXFLAGS="-I${CUDA_HOME}/include"
-
-export LD_LIBRARY_PATH="${MKL_HOME}/lib/intel64_lin:${LD_LIBRARY_PATH}"
-
-BLAS_STATIC_PATH="$MKL_HOME/lib/intel64/libmkl_intel_lp64.a"
-
-ls ${LIB_PATH}/libcublas.so
-ls ${LIB_PATH}/libcudart.so
-
-cat <<EOF
-
-////////////////////////////////////////////////////////////////////////////////
-                                    info
-////////////////////////////////////////////////////////////////////////////////
-
-
-MKL_HOME         = $MKL_HOME
-BLAS_STATIC_PATH = $BLAS_STATIC_PATH
-
-CUDA_ROOT      = ${CUDA_HOME}
-CUDA_LDFLAGS   = "-L${LIB_PATH} -lcuda -L${LIB_PATH} -lcudart -L${LIB_PATH} -lcublas"
-CUDA_CXXFLAGS  = "-I${CUDA_HOME}/include"
-
-
-
-Consider now runnng the following
-
-../configure \\
-  --enable-cuda \\
-  --disable-slice \\
-  --with-blas="-L\$MKL_HOME/lib/intel64/ -lmkl_intel_lp64 -mkl" \\
-  CXX=mpiicpc \\
-  CC=mpiicc \\
-  MPICXX=mpiicpc
-
-
-EOF
-	
-
-return

tools/configure-benches.sh

@@ -98,27 +98,10 @@ EOF
 create_config $tmp only-dgemm
 rm $tmp
 
+#
 # begin doc
 #
-# - cuda-only-dgemm ::
+# - slices-on-gpu-only-dgemm ::
-#   This is the naive CUDA implementation compiling only the dgemm parts
-#   of the compute.
-#
-# end doc
-
-tmp=`mktemp`
-cat <<EOF > $tmp
---enable-cuda
---enable-only-dgemm
---disable-slice
-EOF
-
-create_config $tmp cuda-only-dgemm
-rm $tmp
-
-# begin doc
-#
-# - cuda-slices-on-gpu-only-dgemm ::
 #   This configuration tests that slices reside completely on the gpu
 #   and it should use a CUDA aware MPI implementation.
 #   It also only uses the routines that involve dgemm.
@@ -134,7 +117,7 @@ cat <<EOF > $tmp
 --disable-slice
 EOF
 
-create_config $tmp cuda-slices-on-gpu-only-dgemm
+create_config $tmp sources-in-gpu
 rm $tmp
 
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