2,681 research outputs found
LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing
LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft
Format Abstraction for Sparse Tensor Algebra Compilers
This paper shows how to build a sparse tensor algebra compiler that is
agnostic to tensor formats (data layouts). We develop an interface that
describes formats in terms of their capabilities and properties, and show how
to build a modular code generator where new formats can be added as plugins. We
then describe six implementations of the interface that compose to form the
dense, CSR/CSF, COO, DIA, ELL, and HASH tensor formats and countless variants
thereof. With these implementations at hand, our code generator can generate
code to compute any tensor algebra expression on any combination of the
aforementioned formats.
To demonstrate our technique, we have implemented it in the taco tensor
algebra compiler. Our modular code generator design makes it simple to add
support for new tensor formats, and the performance of the generated code is
competitive with hand-optimized implementations. Furthermore, by extending taco
to support a wider range of formats specialized for different application and
data characteristics, we can improve end-user application performance. For
example, if input data is provided in the COO format, our technique allows
computing a single matrix-vector multiplication directly with the data in COO,
which is up to 3.6 faster than by first converting the data to CSR.Comment: Presented at OOPSLA 201
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