Heterogeneous Parallel Programming | CUDA Programming | GPU Acceleration

Explore the power of GPU-accelerated computing with this comprehensive Coursera course on heterogeneous parallel programming using CUDA.

Introduction

This Coursera course provides an introduction to heterogeneous parallel programming, focusing on the use of CUDA for programming NVIDIA GPUs. The course covers fundamental concepts of parallel computing, CUDA programming model, and optimization techniques for achieving high performance on GPU-accelerated applications.

Highlights

• Introduction to heterogeneous parallel computing and CUDA programming model
• Hands-on experience with CUDA data parallelism, memory management, and kernel-based parallel programming
• Exploration of optimization techniques such as thread scheduling, control divergence, and tiled algorithms
• Coverage of parallel computation patterns like convolution and reduction

Recommendation

This course is recommended for software developers, computer scientists, and researchers interested in leveraging the computational power of GPUs for parallel programming. It provides a solid foundation in heterogeneous parallel programming and equips learners with the skills to develop high-performance GPU-accelerated applications.