The Tensor Algebra Compiler (taco) is a C++ library that computes tensor algebra expressions on sparse and dense tensors. It uses novel compiler techniques to get performance competitive with hand-optimized kernels in widely used libraries for both sparse tensor algebra and sparse linear algebra.
You can use taco as a C++ library that lets you load tensors, read tensors from files, and compute tensor expressions. You can also use taco as a code generator that generates C functions that compute tensor expressions.
Learn more about taco at tensor-compiler.org, in the paper The Tensor Algebra Compiler, or in this talk. To learn more about where taco is going in the near-term, see the technical reports on optimization and formats.
You can also subscribe to the taco-announcements email list where we post announcements, RFCs, and notifications of API changes, or the taco-discuss email list for open discussions and questions.
TL;DR build taco using cmake. Run taco-test in the bin directory.
Build taco using CMake 2.8.3 or greater:
cd <taco-directory>
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j8
To build taco with support for parallel execution (using OpenMP), use the following cmake line with the instructions above:
cmake -DCMAKE_BUILD_TYPE=Release -DOPENMP=ON ..
To build taco for NVIDIA CUDA, use the following cmake line with the instructions above:
cmake -DCMAKE_BUILD_TYPE=Release -DCUDA=ON ..
Please also make sure that you have CUDA installed properly and that the following environment variables are set correctly:
export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
export LIBRARY_PATH=/usr/local/cuda/lib64:$LIBRARY_PATH
If you do not have CUDA installed, you can still use the taco cli to generate CUDA code with the -cuda flag
Run the test suite:
cd <taco-directory>
./build/bin/taco-test
The following sparse tensor-times-vector multiplication example in C++ shows how to use the taco library.
// Create formats
Format csr({Dense,Sparse});
Format csf({Sparse,Sparse,Sparse});
Format sv({Sparse});
// Create tensors
Tensor<double> A({2,3}, csr);
Tensor<double> B({2,3,4}, csf);
Tensor<double> c({4}, sv);
// Insert data into B and c
B.insert({0,0,0}, 1.0);
B.insert({1,2,0}, 2.0);
B.insert({1,2,1}, 3.0);
c.insert({0}, 4.0);
c.insert({1}, 5.0);
// Pack inserted data as described by the formats
B.pack();
c.pack();
// Form a tensor-vector multiplication expression
IndexVar i, j, k;
A(i,j) = B(i,j,k) * c(k);
// Compile the expression
A.compile();
// Assemble A's indices and numerically compute the result
A.assemble();
A.compute();
std::cout << A << std::endl;If you just need to compute a single tensor kernel you can use the taco online tool to generate a custom C library. You can also use the taco command-line tool to the same effect:
cd <taco-directory>
./build/bin/taco
Usage: taco [options] <index expression>
Examples:
taco "a(i) = b(i) + c(i)" # Dense vector add
taco "a(i) = b(i) + c(i)" -f=b:s -f=c:s -f=a:s # Sparse vector add
taco "a(i) = B(i,j) * c(j)" -f=B:ds # SpMV
taco "A(i,l) = B(i,j,k) * C(j,l) * D(k,l)" -f=B:sss # MTTKRP
Options:
...
For more information, see our paper on the taco tools taco: A Tool to Generate Tensor Algebra Kernels.