수학과 최적화

R2026a

병렬 연산으로 선형 대수 및 최적화 문제 해결 가속화

선형 대수 및 최적화 문제 해결을 가속화하기 위해 병렬 연산을 활용합니다. 여기에는 선형 시스템을 푸는 것과 선형, 2차, 원뿔, 정수 및 비선형 최적화 문제를 푸는 것, 그리고 다중 최댓값 또는 최솟값을 갖는 문제에서 전역 해를 탐색하는 것이 포함됩니다.

도움말 항목

선형대수학

Accelerate Solving Linear Equations Using GPU
This example shows how to speed up solving systems of linear equations using a GPU.
GPU에서 희소 형식 배열 사용하기
GPU에서 희소 배열을 사용하는 조건에 대해 배웁니다.
Use Distributed Arrays to Solve Systems of Linear Equations with Direct Methods
This example shows how to solve a system of linear equations of the form $A x = b$ in parallel with a direct method using distributed arrays.
Use Distributed Arrays to Solve Systems of Linear Equations with Iterative Methods
For large-scale mathematical computations, iterative methods can be more efficient than direct methods.

최적화

Parallel Computing in Optimization Toolbox (Optimization Toolbox)
Use multiple processors for optimization.
Testing Parallel Computing (Optimization Toolbox)
Verify that your problem runs correctly in parallel.
Improving Performance with Parallel Computing (Optimization Toolbox)
Investigate factors for speeding optimizations.

전역 최적화

Parallel Computing with MultiStart and GlobalSearch (Global Optimization Toolbox)
Distribute start points across processors with MultiStart, or use parallel gradient estimation with GlobalSearch.
Parallel Computing in Global Optimization Toolbox (Global Optimization Toolbox)
Use multiple processors to speed optimization.
Optimize ODEs in Parallel (Global Optimization Toolbox)
Save time by calling an expensive subroutine just once and computing an ODE solution in parallel using patternsearch or ga.

추천 예제

Solve Differential Equation Using Multigrid Preconditioner on Distributed Discretization

Solve Poisson's equation using a preconditioned iterative solver and distributed arrays. By using distributed arrays, you can scale up the calculation using the memory of a cluster of machines, not just the memory of a single machine. You can scale up without changing your code.