Highlights of the GPU Programming Certification Program from Brainmeasures

The comprehensiveness and detailed nature of the GPU Programming certification program developed by Brainmeasures are among the major reasons that attracts the experts and researchers of this field. The course is designed by the experts of computer graphics with strong background of electronics and IT. So, don’t miss this opportunity and get enrollment in the course after registering yourself at Brainmeasures if you want to go through its detailed syllabus with study guidelines. Mentioned below are some important topics of the course that you will study during the journey of GPU Programming at Brainmeasures:

• Introduction to GPU Programming
• Major uses of GPU Programming
• What are different programming techniques for GPU
• How GPU Programming can be best utilized in open source environment
• Introduction about CUDA
• How CUDA handbook library can be used efficiently and effectively for GPU Programming
• Understanding about different coding styles and CUDA software development toolkit
• Guidelines about hardware architecture
• Front-end and back-end functions
• Integration with GPUs and role of multiple GPUs
• A brief introduction about virtual addressing
• Mapping techniques
• Difference between CPU/GPU environment
• How CPU and GPU interact with each other
• GPU architecture and synchronization procedure
• Inter and intra GPU platforms
• Software layering and architecture synchronization with GPU
• GPU Programming and processing in absence of CUDA
• CUDA driver and API
• What is cuodjdump and nvidia-smi
• What are different command line tools
• Key pairing procedure
• EC2 and it environment for Linux and Windows
• Memory types and mapping techniques
• How to enhance and optimize memory bandwidth
• Correction codes for errors (ECC)
• What is the difference between constant and access memory and how to use them efficiently and effectively
• Streaming and events handling in GPU Programming
• CPU/GPU synchronization and blocking events
• What is the syntax for kernel execution
• Coherent and cache analysis
• Streaming multiprocessors procedure
• Concept of memory and registers
• What is funnel shift
• Role of floating point support
• Understanding about different types of precisions (i.e. single, double and half)
• Conditional coding for prediction, divergence and convergence
• What are the different types of primitives
• Working with multiple GPUs and how to program them efficiently
• Peer-to-Peer memory copy and addressing procedure
• Texturing and its procedure in GPU Programming
• Effectively use 2D and 3D texturing
• How to efficiently manage the streaming workloads
• Understanding about scan and circuit design
• CUDA and reduce then scan strategies
• What is instructions counts and stream compaction
• Understanding about the concept of Naïve forecasting and implementation in GPU Programming
• Scalability and CPU optimization
• Image processing techniques
• Complete guide for CUDA and its environment