- Nov 26, 2019
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Lukas Cejka authored
Implemented for the benchmark to write the output of MatrixReader into the log file. BUG: Every other error message added into the Benchmark doesn't have a '!' as a prefix in the log file.
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
Changed TYPED_TEST_CASE to TYPED_TEST_SUITE, as per google test recommendation which said that TYPED_TEST_CASE is deprecated.
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Lukáš Matthew Čejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
Copied tnl-benchmark-spmv files and spmv.h from BLAS to SpMV. Deleted min/max size and stepFactor. Not working yet, backup purposes.
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Lukas Cejka authored
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Lukas Cejka authored
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Lukas Cejka authored
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- Nov 10, 2019
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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- Nov 08, 2019
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Jakub Klinkovský authored
Refactoring for execution policies Closes #49, #46, and #11 See merge request !42
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
Closes #49
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Jakub Klinkovský authored
They are not suitable for more than 2 devices/execution types; their design breaks the Open-Closed Principle. Instead, a type template "Self" was created, which allows to change any template parameter.
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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- Oct 25, 2019
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
Serialization in TNL::File: File::save and File::load are specialized by Allocator instead of Device
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Jakub Klinkovský authored
The usage of algorithms such as MemoryOperations or Reduction is not bound to a particular container. On the other hand, ArrayIO, ArrayAssignment, VectorAssignment and StaticArrayAssignment are just implementation details for the containers - moved into TNL/Containers/detail/ Also moved ParallelFor, StaticFor, StaticVectorFor, TemplateStaticFor into TNL/Algorithms/
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Jakub Klinkovský authored
This will be necessary to avoid code bloat with more than 2 devices (execution types).
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Jakub Klinkovský authored
- cudaMemcpy is slower than our ParallelFor kernel for CUDA - use std::copy and std::equal instead of memcpy and memcmp, but only as sequential fallbacks - use parallel algorithms for containsValue and containsOnlyValue (again with sequential fallbacks)
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Jakub Klinkovský authored
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