DOWNLOAD A FREE TRIALWhat Is Parallel Computing?
Parallel computing is a powerful technique that harnesses the combined processing power of multiple processors or computers to solve problems simultaneously. Imagine splitting a large task into smaller chunks and solving them concurrently, significantly reducing processing time.
Solve computationally and data intensive problems using multicore processors, GPUs, and compute clusters. You can:
- Leverage all compute resources
- Parallelize MATLAB® applications using high-level constructs
- Use NVIDIA® GPUs directly from MATLAB
- Run multiple Simulink® simulations in parallel
- Prototype on the desktop and scale to clusters and clouds
“Using Parallel Computing Toolbox we added four lines of code and wrote some simple task management scripts. Simulations that took months now run in a few days. MathWorks parallel computing tools enabled us to capitalize on the computing power of large clusters without a tremendous learning curve.” – Diglio Simoni, RTI
Using Parallel Computing with MATLAB and Simulink
Desktop Parallel Computing for CPU and GPU
Parallel Computing Toolbox™ lets you take control of your local multicore processors and GPUs to speed up your work. High-level constructs enable you to parallelize MATLAB applications without CUDA® or MPI programming and run multiple Simulink simulations in parallel. Several MATLAB and Simulink products let you take advantage of your compute resources by setting a flag or preference. You can use the full processing power of multicore desktops by executing applications on workers (MATLAB computational engines) that run locally using Parallel Computing Toolbox. Prototype your applications and simulations on the desktop and then scale to clusters and clouds using MATLAB Parallel Server™ without recoding.
Scale MATLAB and Simulink on Clusters and in the Cloud
MATLAB Parallel Server enables you to scale MATLAB programs and Simulink simulations to clusters and clouds. You can develop and prototype your programs and simulations on your desktop with Parallel Computing Toolbox and then run them on clusters and clouds without recoding. MATLAB Parallel Server runs your programs and simulations as scheduled applications on your cluster using the MATLAB optimized scheduler provided by MATLAB Parallel Server or your own scheduler.
TechSource Asia: Your Parallel Computing Partner
At TechSource Asia, we offer a comprehensive suite of parallel computing solutions to empower businesses of all sizes:
- Hardware and Software Solutions: We provide expert guidance on selecting the right hardware (multi-core processors, GPUs, compute clusters) and software (MATLAB Parallel Computing Toolbox, OpenMP) to meet your specific needs.
- Parallel Programming Expertise: Our team of experienced developers can assist you with parallelizing your existing code or developing new applications that leverage parallel computing techniques.
- Performance Optimization: We help you optimize your parallel computing environment for maximum efficiency and performance.
Applications of Parallel Computing
Parallel computing finds application in a wide range of industries and tasks, including:
- Scientific Computing: Simulate complex physical phenomena, analyze large datasets in fields like astronomy, weather forecasting, and drug discovery.,
- Financial Modeling: Perform complex financial simulations and risk assessments at high speeds.
- Machine Learning and AI: Train machine learning models and artificial intelligence algorithms significantly faster.
- Big Data Analytics: Analyze massive datasets efficiently to uncover hidden patterns and insights.
Embrace the Future of Computing
By incorporating parallel computing into your operations, you can gain a significant competitive edge. TechSource Asia is your trusted partner in harnessing the power of parallel computing. Contact us today to discuss your specific requirements and explore how we can help you accelerate your data processing and analysis capabilities.
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