Torch alternatives and similar libraries
Based on the "Scientific Computing" category.
Alternatively, view Torch alternatives based on common mentions on social networks and blogs.
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FFTW
DO NOT CHECK OUT THESE FILES FROM GITHUB UNLESS YOU KNOW WHAT YOU ARE DOING. (See below.) -
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Kratos Multiphysics
Kratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is written in C++ with extensive Python interface. -
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preCICE
A coupling library for partitioned multi-physics simulations, including, but not restricted to fluid-structure interaction and conjugate heat transfer simulations. -
HELICS
Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) -
Units
A run-time C++ library for working with units of measurement and conversions between them and with string representations of units and measurements -
itpp
IT++ library mirror/fork. C++ library of mathematical, signal processing and communication classes and functions. -
suanPan
🧮 An Open Source, Parallel and Heterogeneous Finite Element Analysis Framework -
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Dimwits
A compact C++ header-only library providing compile-time dimensional analysis and unit awareness
Access the most powerful time series database as a service
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
Development Status
Torch is not in active developement. The functionality provided by the C backend of Torch, which are the TH, THNN, THC, THCUNN libraries is actively extended and re-written in the ATen C++11 library (source, mirror). ATen exposes all operators you would expect from torch7, nn, cutorch, and cunn directly in C++11 and includes additional support for sparse tensors and distributed operations. It is to note however that the API and semantics of the backend libraries in Torch-7 are different from the semantice provided by ATen. For example ATen provides numpy-style broadcasting while TH* dont. For information on building the forked Torch-7 libraries in C, refer to "The C interface" in pytorch/aten/src/README.md.
Need help?
Torch7 community support can be found at the following locations. As of 2019, the Torch-7 community is close to non-existent.
- Questions, Support, Install issues: Google groups
- Reporting bugs: torch7 nn cutorch cunn optim threads
- Hanging out with other developers and users (strictly no install issues, no large blobs of text): Gitter Chat
Torch Package Reference Manual
Torch is the main package in Torch7 where data structures for multi-dimensional tensors and mathematical operations over these are defined. Additionally, it provides many utilities for accessing files, serializing objects of arbitrary types and other useful utilities.
Torch Packages
- Tensor Library
- [Tensor](doc/tensor.md) defines the all powerful tensor object that provides multi-dimensional numerical arrays with type templating.
- [Mathematical operations](doc/maths.md) that are defined for the tensor object types.
- [Storage](doc/storage.md) defines a simple storage interface that controls the underlying storage for any tensor object.
- File I/O Interface Library
- [File](doc/file.md) is an abstract interface for common file operations.
- [Disk File](doc/diskfile.md) defines operations on files stored on disk.
- [Memory File](doc/memoryfile.md) defines operations on stored in RAM.
- [Pipe File](doc/pipefile.md) defines operations for using piped commands.
- [High-Level File operations](doc/serialization.md) defines higher-level serialization functions.
- Useful Utilities
- [Timer](doc/timer.md) provides functionality for measuring time.
- [Tester](doc/tester.md) is a generic tester framework.
- [CmdLine](doc/cmdline.md) is a command line argument parsing utility.
- [Random](doc/random.md) defines a random number generator package with various distributions.
- Finally useful [utility](doc/utility.md) functions are provided for easy handling of torch tensor types and class inheritance.