Dew.Math.Linux
6.3.5
dotnet add package Dew.Math.Linux --version 6.3.5
NuGet\Install-Package Dew.Math.Linux -Version 6.3.5
<PackageReference Include="Dew.Math.Linux" Version="6.3.5" />
<PackageVersion Include="Dew.Math.Linux" Version="6.3.5" />
<PackageReference Include="Dew.Math.Linux" />
paket add Dew.Math.Linux --version 6.3.5
#r "nuget: Dew.Math.Linux, 6.3.5"
#:package Dew.Math.Linux@6.3.5
#addin nuget:?package=Dew.Math.Linux&version=6.3.5
#tool nuget:?package=Dew.Math.Linux&version=6.3.5
Dew.Math.Linux
High-performance vectorized numerical computation library for Linux
Dew.Math.Linux is the Linux-native accelerated edition of the Dew.Math numerical library. It provides high-performance matrix and vector computation using native BLAS/LAPACK acceleration, multithreading, and CPU feature dispatch. It is designed for HPC compute nodes, scientific servers, simulation engines, data processing pipelines, microservices, and cloud container deployments where Linux is the primary execution environment.
Core Numerical Capabilities
Dense Linear Algebra
- BLAS/LAPACK-based linear algebra with native acceleration
- Decompositions: SVD, QR, LQ, LU, eigenvalue problems, least-squares, rank-revealing methods
- Complex-valued matrices and vectorized complex arithmetic
- High-throughput matrix multiplication and factorization kernels
Sparse Matrix Computing
- Sparse matrix formats suitable for large systems
- Direct sparse solvers: Pardiso and UMFPACK
- Krylov-based iterative solvers: CG, BiCG, GMRES, and variants
- Preconditioning support for improved convergence stability
Optimization and Modeling
- Non-linear curve fitting (Levenberg-Marquardt and trust-region variants)
- Linear programming and constrained optimization
- Numerical root solving and non-linear system solution
Probability and Statistical Methods
- Random number generators for multiple probability distributions
- CDF/PDF evaluation and stochastic sampling
- Monte Carlo workflows and statistical summaries
Polynomial and Analytical Math
- Polynomial evaluation, interpolation, piecewise polynomial models, and spline fitting
- Numerical integration and differentiation routines
- Special functions including Airy, Bessel, Gamma-related, Legendre and elliptic integrals
Performance Architecture
- Native Linux BLAS/LAPACK acceleration
- CPU dispatching for AVX2 and AVX-512 instruction sets
- Scalable multithreading with low-GC pressure memory pool
- Capacity-based memory model to minimize allocation overhead
- Subranges (views) allow slicing matrix and vector memory without copying
- Optional OpenCL GPU compute integration (where supported)
Typical workloads see significant acceleration compared to purely managed math implementations.
Platform and Deployment Model
Dew.Math.Linux contains Linux-native runtime binaries.
Supported Linux Distributions (glibc-based):
- Red Hat Enterprise Linux (RHEL) 7.x, 8.x, 9.x
- Rocky Linux 7.x, 8.x, 9.x
- AlmaLinux 7.x, 8.x, 9.x
- CentOS 7.x (legacy), CentOS Stream 8 and 9
- Ubuntu and Debian (when glibc version matches above compatibility levels)
Deployment Environments
- HPC clusters (SLURM / PBS / LSF / Kubernetes batch compute nodes)
- Scientific Linux compute nodes
- Cloud compute machines (AWS, Azure, GCP)
- Docker / Podman / Kubernetes container images (no extra runtime installer required)
- On-prem microservice pipelines and model-serving backends
Drop-in Replaceable Architecture (Important)
Dew.Math.Linux shares the same namespaces and class layout as:
- Dew.Math (Windows accelerated)
- Dew.Math.Core (managed-only)
This allows switching runtime editions without modifying your source code.
Example workflow:
- Develop on Windows using Dew.Math.Core or Dew.Math.
- For Linux deployment, uninstall the Windows package and install Dew.Math.Linux.
- Rebuild. No code changes required.
No conditional compilation. No dual code paths. No API differences.
Package Relationship
| Package | Platform | Acceleration Model |
|---|---|---|
| Dew.Math | Windows | Native AVX2 / AVX-512 acceleration |
| Dew.Math.Linux | Linux | Native AVX2 / AVX-512 acceleration |
| Dew.Math.Core | All | Managed-only (portable, no native) |
Advanced Memory Model
- Vectors and Matrices expose a Capacity property to reduce allocation count
- Subrange support allows nested view-based operations without copying
- Object pool provides thread-local memory caching with minimal allocator contention
- Designed for high concurrency and deterministic performance under parallel workloads
- Nearly all math operations avoid internal memory allocations
Trial Version Usage on Linux
The trial version of Dew.Math.Linux must run under a debugger.
Since Visual Studio is not available on Linux, use one of the following:
- Visual Studio Code with the .NET debugger extension
- JetBrains Rider with debugging enabled
Running outside a debugger (for example, as a service or from command line) triggers evaluation mode.
Examples
(While UI samples are Windows-based, the computation API is the same on Linux.)
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 6-9) examples: https://github.com/Dew-Research/DewLabStudio-NETCore-Samples
Documentation
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
License
Commercial license. See DewMathLicense.txt included in this package. All Dew.* NuGet packages on nuget.org are trial versions and require running inside a debugger.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 is compatible. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-windows was computed. |
| .NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
| .NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | tizen40 was computed. tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
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.NETStandard 2.0
- No dependencies.
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net8.0
- No dependencies.
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net9.0
- No dependencies.
NuGet packages (3)
Showing the top 3 NuGet packages that depend on Dew.Math.Linux:
| Package | Downloads |
|---|---|
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Dew.Signal.Linux
Dew.Signal.Linux is the Linux-native accelerated edition of the Dew.Signal digital signal processing library. It provides a full suite of DSP algorithms built on top of Dew.Math.Linux, delivering high-performance numerical processing with multithreaded AVX/AVX2/AVX-512 hardware acceleration. This package is intended for scientific servers, compute clusters, HPC pipelines, digital instrumentation, real-time data acquisition, industrial analytics, embedded Linux platforms, and cloud CPU workloads. Filter Design and Processing: - IIR filters: Butterworth, Chebyshev I/II, Elliptic, Bessel - Transformations: bilinear, matched-Z, frequency remapping, pole-zero and state-space formulations - FIR filters: window methods, Remez exchange, Hilbert transformers, differentiators, integrators, Savitzky–Golay smoothers, envelope detection - Multirate DSP: decimation, interpolation, half-band polyphase filters, zoom-spectrum workflows Spectral and Frequency-Domain Analysis: - FFT-based spectral estimation and spectrum analyzer infrastructure - Parametric estimators: Yule–Walker, Burg, Covariance, Modified Covariance - Chirp-Z transform, time-frequency spectrograms, bispectrum, bicoherence, coherence, transfer function estimation, phase unwrapping - Real/complex cepstrum and inverse cepstrum - Spectral statistics: noise floor, SFDR, THD, THDN, SINAD, RMS, SNR Signal Modeling, Streaming, and Synthesis: - White, pink, brownian, blue, violet and deterministic test signal generators - Continuous streaming components and dataflow processing units for real-time measurement systems - High-performance convolution, correlation, DCT/IDCT, interpolation and filtering kernels - Spectral forecasting based on controlled peak selection Integration and Platform Model: - Uses Dew.Math.Linux for native-accelerated numerical backend - Does **not** require WinForms or TeeChart (visualization is optional and external) - Suitable for server, embedded, batch compute, containerized, and headless execution Dew.Signal.Linux provides the same API surface as Dew.Signal, but is optimized specifically for Linux compute environments where high throughput and deterministic performance are required. |
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Dew.Stats.Linux
Dew.Stats.Linux is the Linux-native accelerated edition of the Dew.Stats statistical computing library. It provides a comprehensive suite of tools for probability distributions, hypothesis testing, regression, multivariate analysis, experimental design, and time-series modeling, powered by the high-performance vectorized numerical backend in Dew.Math.Linux. This edition is designed for Linux-based compute servers, HPC pipelines, analytics microservices, research clusters, data acquisition systems, and real-time industrial environments. Statistical Capabilities: - Probability distributions (PDF, CDF, inverse CDF) for 36+ discrete and continuous models - Random number generators and parameter estimation - Descriptive statistics, histograms, ogives, quantiles, outlier analysis Hypothesis Testing and Inference: - Parametric tests (t, Z, F, Chi-Squared, Bartlett, Hotelling T²) - Non-parametric tests (Wilcoxon, Sign, Mann–Whitney, Anderson–Darling, Shapiro–Wilk, KS) - Confidence intervals, residual diagnostics, model fitness evaluation Regression and Statistical Modeling: - Linear, multiple linear, logistic, Poisson, ridge and nonlinear regression - ANOVA and ANCOVA - Principal Component Regression and regularization workflows Multivariate and Structural Analysis: - PCA (correlation/covariance) with eigen decomposition - PCA residuals, factor rotation, Bartlett tests, item analysis - Classical Multidimensional Scaling and dimensionality interpretation Time Series Modeling and Forecasting: - ACF and PACF analysis - ARMA, ARIMA and ARAR models - Exponential smoothing (single/double/triple) - Box-Ljung significance testing and forecasting evaluation High-Level Statistical Workflow Components: - TMtxANOVA, TMtxMulLinReg, TMtxNonLinReg, TMtxPCA, TMtxHypothesisTest, TMtxBinaryTest, TMtxMDScaling Platform Characteristics: - Uses **Dew.Math.Linux** for native BLAS/LAPACK acceleration with AVX2/AVX512 dispatch - Highly scalable under multi-threaded workloads - No Windows or WinForms dependencies - Headless execution suitable for batch, service, and compute-node environments Dew.Stats.Linux provides the full analytical capabilities of Dew.Stats, optimized specifically for Linux-based CPU compute environments. |
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Dew.Lab.Studio.Linux
Dew.Lab.Studio.Linux bundles the native-accelerated Linux editions of the Dew libraries: Dew.Math.Linux, Dew.Signal.Linux, and Dew.Stats.Linux. This package is intended for Linux desktops, servers, HPC clusters, and container-based compute environments requiring high numerical throughput and scalable parallel execution. Included Components: - Dew.Math.Linux: dense and sparse linear algebra (BLAS/LAPACK, Pardiso, UMFPACK), complex arithmetic, interpolation and splines, spectral and polynomial transforms, optimization, curve fitting, special function library, numerical integration/differentiation - Dew.Signal.Linux: FIR/IIR filtering, FFT and spectral analysis, convolution/correlation, windowing, resampling, time-frequency transforms, streaming-friendly DSP operations - Dew.Stats.Linux: probability distributions, random sampling, inference tests, regressions, statistical modeling and simulation workflows Performance Architecture: - Native-accelerated BLAS/LAPACK for Linux - CPU feature dispatch (AVX / AVX2 / AVX-512) - Scalable multithreading with low-GC memory allocator - Optional OpenCL GPU acceleration when available Use Dew.Lab.Studio.Linux when you require a unified math + DSP + statistics environment on Linux, with full native acceleration and container/HPC-friendly runtime deployment. |
GitHub repositories
This package is not used by any popular GitHub repositories.