Dew.Math
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.
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