3 个仓库
Awesome GitHub RepositoriesPerformance Accelerators
Utilities for accelerating numerical computations through sparsity detection, matrix coloring, and hardware offloading.
Distinct from Nonlinear Optimization Solvers: Distinct from Nonlinear Optimization Solvers: focuses on general performance acceleration techniques for solvers rather than specific nonlinear optimization algorithms.
Explore 3 awesome GitHub repositories matching scientific & mathematical computing · Performance Accelerators. Refine with filters or upvote what's useful.
Awesome Performance Accelerators GitHub Repositories
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- ceres-solver/ceres-solver
ceres-solver/ceres-solver
4,499在 GitHub 上查看Ceres Solver 是一个 C++ 数值优化库，专注于非线性最小二乘法和无约束优化问题。它作为一个自动微分和鲁棒曲线拟合框架，提供了求解大规模数学模型的工具。 该库以其光束法平差 (bundle adjustment) 能力而著称，利用稀疏矩阵结构来优化 3D 场景点和相机参数。它利用双数自动微分来计算代价函数的导数，无需手动推导雅可比矩阵。 该项目涵盖了广泛的优化功能，包括非欧几里得空间的流形约束、用于减轻异常值的鲁棒损失函数，以及稠密和稀疏线性系统求解。它还提供了用于旋转表示转换、表格数据插值和参数协方差估计的实用工具。 提供针对 Android 和 iOS 目标的构建配置，以支持移动硬件优化。
Optimizes memory and computation when the structural patterns of data change during the optimization process.
C++ - sciml/differentialequations.jl
SciML/DifferentialEquations.jl
3,121在 GitHub 上查看DifferentialEquations.jl is a comprehensive numerical library designed for solving ordinary, stochastic, delay, and algebraic differential equations. It functions as a high-performance solver suite that integrates scientific machine learning, probabilistic programming, and automated differentiation into a unified framework. By leveraging multiple dispatch and symbolic-numeric integration, the library provides a flexible environment for complex mathematical modeling and simulation. The project distinguishes itself through its ability to bridge traditional numerical analysis with modern machine
Accelerates complex computations through automated sparsity detection, matrix coloring, and hardware offloading.
Juliadaeddedelay-differential-equations - juliasymbolics/symbolics.jl
JuliaSymbolics/Symbolics.jl
1,514在 GitHub 上查看Symbolics.jl is a foundational framework for symbolic mathematics, automated differentiation, and scientific compilation within the Julia programming language. It provides a comprehensive system for algebraic manipulation, expression simplification, and the construction of mathematical models, enabling users to represent complex physical and chemical systems as symbolic equations. The library distinguishes itself through a source-to-source compilation engine that translates high-level symbolic representations directly into optimized, parallelized, and hardware-specific numerical code. By util
Provides automated sparsity detection for Jacobians and Hessians to skip zero-value computations during numerical execution.
Juliacascomputer-algebra-systemhigh-performance
