מלאו את הטופס והשאירו פרטים, נציגת הקורסים שלנו תחזור אליכם עם מידע נוסף על הקורס.

קורס בנושא:

Accelerating and Parallelizing MATLAB Code

נושאי הקורס:

  • Improving Performance
    Objective: Analyze code performance and utilize techniques for acceleration within MATLAB.

    • Identifying bottle necks
    • Preallocating arrays
    • Vectorizing operations in various ways
    • Rewriting algorithms

    Generating MEX-Files

    Objective: Generate compiled code files from MATLAB code for better performance.

    • MATLAB Coder overview and workflow
    • Generating and verifying MEX-files
    • Calling unsupported functions
    • Adjusting settings for MEX-file generation

    Parallelizing Computations

    Objective: Parallelize code execution to take advantage of multiple cores.

    • Opening additional MATLAB processes
    • Running parallel for-loops
    • Measuring speedup
    • Processing multiple files in parallel

Parallel for-Loops

Objective: Explore parallel for-loops in more detail and apply techniques for converting for-loops to parfor-loops.

  • Requirements of parallel for-loops
  • Parallelizing for-loops
  • Retrieving intermediate results

Offloading Execution

Objective: Offload computations to another MATLAB process in order to be able to use MATLAB for other tasks in the meantime. This is also a preparation step for working with clusters.

  • Processing in batch
  • Creating batch jobs
  • Retrieving results
  • Using the Job Monitor

Working with Clusters

Objective: Accelerate computations and realize more extensive simulations by utilizing multiple computers.

  • Local and remote clusters
  • Dynamic licensing
  • Cluster discovery and connection
  • File access considerations

GPU Computing

Objective: Execute MATLAB code on your computer’s graphics card (GPU) as another option for speeding up calculations.

  • Overview of GPU architecture and processing
  • Applications suitable for GPU processing
  • Invoking MATLAB functions on the GPU
  • Using pre-existing CUDA code