Overview of MTL4: The Matrix Template Library 4 incorporates the most modern programming techniques to provide an easy and intuitive interface to users while enabling optimal performance. The natural mathematical notation in MTL4 empowers all engineers and scientists to implement their algorithms and models in minimal time. All technical aspects are encapsulated in the library. This has two fundamental advantages: Not worrying about technical details speeds up scientific and engineering software development tremendously. Not hard-wiring hardware features in application allows for easy porting to new platforms.
Keywords for this software
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Byfut, Andreas; Schröder, Andreas: Unsymmetric multi-level hanging nodes and anisotropic polynomial degrees in (H^1)-conforming higher-order finite element methods (2017)
- De La Cruz, Luis M.; Ramos, Eduardo: General template units for the finite volume method in box-shaped domains (2016)
- Demidov, Denis; Ahnert, Karsten; Rupp, Karl; Gottschling, Peter: Programming CUDA and OpenCL: a case study using modern C++ libraries (2013)
- Denis, Christophe; Montan, Sethy: Numerical verification of industrial numerical codes (2012)
- Vidović, D.; Dimkić, M.; Pušić, M.: Accelerated non-linear finite volume method for diffusion (2011)
- Logg, Anders; Wells, Garth N.: DOLFIN: automated finite element computing (2010)
- Brčić, Stanko; Žugić-Zornija, Ljiljana: Simple and effective C++ matrix-vector library for nonprofessionals in computer science (2009)
- Gottschling, Peter; Wise, David S.; Joshi, Adwait: Generic support of algorithmic and structural recursion for scientific computing (2009)
- Manzini, G.; Mazet, S.: An object-oriented interface for the dynamic memory management of sparse discrete mathematical operators in numerical scientific applications (2002)
- Press, William H.; Teukolsky, Saul A.; Vetterling, William T.; Flannery, Brian P.: Numerical recipes in C/C++. The art of scientific computing. Code CD-ROM v 2. 11 with Windows or Macintosh single-screen license. (2002)
- Valsalam, Vinod; Skjellum, Anthony: A framework for high-performance matrix multiplication based on hierarchical abstractions, algorithms and optimized low-level kernels (2002)
Further publications can be found at: http://www.simunova.com/node/151