Acceleration
To speed up your code while prototyping, you can:
Leverage multiple cores or workers by using the
parforfunction.Run your code on a GPU. Typically, you transfer data to the GPU by using the
gpuArray(Parallel Computing Toolbox) function and then retrieve the output data from the GPU by using thegather(Parallel Computing Toolbox) function. For a list of Communications Toolbox™ features, see Functions and System Objects Supporting GPU Arrays.Run your simulation on a cloud or in a cluster with multiple workers. For more information, see MathWorks Cloud Center (Parallel Computing Toolbox).
Functions
Topics
- Accelerate Simulation Using GPUs
Speed up your communications system simulation using GPUs.
Featured Examples
Accelerate Ray Tracing Analysis Using GPU
Perform accelerated ray tracing analysis using a GPU.
Accelerate MIMO-OFDM Link Simulation Using GPU
Accelerate a MIMO-OFDM link simulation with LDPC channel coding by using a GPU.
Simulation Acceleration Using MATLAB Coder and Parallel Computing Toolbox
Ways to accelerate the simulation of communications algorithms in MATLAB.
Accelerate SISO Single-Carrier Link Simulation Using GPU
Compare four techniques to accelerate SISO single-carrier link bit error rate (BER) simulations.
Using GPUs to Accelerate Turbo Coding Bit Error Rate Simulations
Use GPUs to dramatically accelerate bit error rate simulations.
LDPC Link Simulation Using GPU Processing
Use the ldpcDecode function and gpuArray to increase the speed of a communications system simulation.
5G LDPC Block Error Rate Simulation Using the Cloud or a Cluster
Use the cloud or a cluster for block error rate (BLER) simulation of low-density parity-check (LDPC) coding for the 5G NR downlink shared transport channel (DL-SCH).
