Dew.Math is the Windows-optimized high-performance numerical computation library for .NET. It provides a vectorized matrix and vector math environment with native runtime acceleration, multithreaded execution, and extensive algorithm libraries for scientific, engineering, financial, AI/ML and signal processing workloads. Core Numerical Capabilities: - Dense linear algebra (BLAS, LAPACK): SVD, QR, LQ, LU, eigenvalue problems, least-squares, rank reveals - Sparse matrix support: direct solvers (Pardiso, UMFPACK), iterative solvers (CG, BiCG, GMRES), preconditioning strategies, structured sparse formats - Complex number computation with fully vectorized math operations - Polynomial arithmetic, interpolation, splines, rational approximations, Chebyshev basis transforms - Numerical differentiation, root solving, non-linear systems, ODE support for stiff and non-stiff cases - Probability distributions (over 30 families), random number generators, Monte Carlo methods - Special mathematical functions (Airy, Bessel, Gamma-related, elliptic integrals, Legendre, etc.) Optimization and Modeling: - Non-linear curve fitting with Levenberg-Marquardt and trust-region refinements - Direct and constrained optimization (Simplex/Nelder–Mead, BFGS, Conjugate Gradient, LP, dual-phase simplex, Gomory cutting plane) - Vectorized expression parser for dynamic formula construction and symbolic-style evaluation Performance Architecture: - Native accelerated BLAS/LAPACK kernels with automatic CPU dispatch (AVX, AVX2, AVX-512) - Scalable multithreading with a lock-free memory allocator for low-GC overhead - Optional OpenCL GPU offloading for supported device targets Platform Model: - Contains Windows native acceleration binaries - For Linux native acceleration use: Dew.Math.Linux - For a pure managed, portable edition use: Dew.Math.Core Use Dew.Math when you require **maximum numerical performance on Windows** for HPC, simulation, economic modeling, data analytics, or scientific visualization workflows.
High-performance vectorized numerical computation library for .NET
Dew.Math is a high-performance numerical math library for .NET, providing a vectorized matrix and vector computation environment with native runtime acceleration on modern CPUs. It is designed for scientific computing, engineering, signal and system modeling, optimization, simulation, financial modeling, and data analysis applications that require deterministic performance and high throughput.
Typical real-world performance improvement over pure C# implementations ranges 5x to 50x, depending on workload characteristics.
| Package | Purpose / Platform | Acceleration Model |
|---|---|---|
| Dew.Math | Windows | Native acceleration (AVX2 / AVX-512) |
| Dew.Math.Linux | Linux | Native acceleration (AVX2 / AVX-512) |
| Dew.Math.Core | Cross-platform (portable) | Managed-only (no native runtime) |
Important notes:
All three variants share:
This allows platform switching with no code changes.
Typical workflow:
Or:
No conditional compilation, no API branching, no code rewrite.
| Package | UI Toolkit | Platform | TeeChart Edition Used | Purpose |
|---|---|---|---|---|
| Dew.Math.Tee | WinForms | .NET Framework 4.8 only | TeeChart Lite (free, bundled) | Basic high-speed visualization |
| Dew.Math.TeePro | WinForms | .NET Framework 4.8, .NET 8/9 Win. | TeeChart.NET (commercial license) | Advanced full-featured visualization |
Dew Research GitHub Home: https://github.com/Dew-Research
WinForms / WPF / ASP.NET (.NET Framework) examples: https://github.com/Dew-Research/DewLabStudio-NETFramework-Samples
WinForms (.NET Core / .NET 6-9) examples: https://github.com/Dew-Research/DewLabStudio-NETCore-Samples
API Reference: https://www.dewresearch.com/Help/VSNET/MtxVec/contents.html
User Guide (PDF): http://downloads.dewresearch.com/downloads/MtxVecV6-CSharp.pdf
Product Page: https://www.dewresearch.com/products/mtxvec
NuGet Publisher Profile: https://www.nuget.org/profiles/DewResearch
License: https://www.dewresearch.com/downloads/LicenseNET.pdf
Commercial license. See DewMathLicense.txt included in this package. All Dew.* NuGet packages on nuget.org are trial versions and work only inside Visual Studio IDE.
FAQs
Dew.Math is the Windows-optimized high-performance numerical computation library for .NET. It provides a vectorized matrix and vector math environment with native runtime acceleration, multithreaded execution, and extensive algorithm libraries for scientific, engineering, financial, AI/ML and signal processing workloads. Core Numerical Capabilities: - Dense linear algebra (BLAS, LAPACK): SVD, QR, LQ, LU, eigenvalue problems, least-squares, rank reveals - Sparse matrix support: direct solvers (Pardiso, UMFPACK), iterative solvers (CG, BiCG, GMRES), preconditioning strategies, structured sparse formats - Complex number computation with fully vectorized math operations - Polynomial arithmetic, interpolation, splines, rational approximations, Chebyshev basis transforms - Numerical differentiation, root solving, non-linear systems, ODE support for stiff and non-stiff cases - Probability distributions (over 30 families), random number generators, Monte Carlo methods - Special mathematical functions (Airy, Bessel, Gamma-related, elliptic integrals, Legendre, etc.) Optimization and Modeling: - Non-linear curve fitting with Levenberg-Marquardt and trust-region refinements - Direct and constrained optimization (Simplex/Nelder–Mead, BFGS, Conjugate Gradient, LP, dual-phase simplex, Gomory cutting plane) - Vectorized expression parser for dynamic formula construction and symbolic-style evaluation Performance Architecture: - Native accelerated BLAS/LAPACK kernels with automatic CPU dispatch (AVX, AVX2, AVX-512) - Scalable multithreading with a lock-free memory allocator for low-GC overhead - Optional OpenCL GPU offloading for supported device targets Platform Model: - Contains Windows native acceleration binaries - For Linux native acceleration use: Dew.Math.Linux - For a pure managed, portable edition use: Dew.Math.Core Use Dew.Math when you require **maximum numerical performance on Windows** for HPC, simulation, economic modeling, data analytics, or scientific visualization workflows.
We found that dew.math demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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