CUDA Training Course Online

SKU: 2279
9 Lesson
|
40 Hours
igmGuru offers the best CUDA programming training online worldwide. This comprehensive training program covers key topics such as the CUDA architecture, parallel computing fundamentals, thread management, memory hierarchies, and efficient execution strategies. The course also dives into critical concepts like kernel programming, synchronization techniques, performance optimization, and utilizing CUDA libraries like cuBLAS, cuFFT, and cuDNN for optimized tasks. This certification course includes in-depth modules on multi-GPU programming, asynchronous execution using CUDA streams, debugging and profiling GPU code, and real-world applications of CUDA in fields like machine learning, data processing, and scientific computing.

Overview

These CUDA course modules are designed by industry experts to reflect real-world computing challenges, best practices, and the latest developments in high-performance GPU computing. Enroll now in our CUDA Programming certification course today and prepare for the official exam to become a certified professional.

Prerequisites:

  • Good knowledge of C/C++ programming
  • Basic understanding of parallel programming concepts
  • Familiarity with GPU architecture and memory hierarchy
  • Comfort with Linux or Windows command line
  • Basic understanding of computer architecture

What You Will Learn

  1. Write parallel programs using CUDA's thread, block, and grid structure.
  2. Manage memory efficiently (global, shared, constant memory).
  3. Optimize performance with techniques like memory coalescing and access patterns.
  4. Utilize CUDA libraries for specialized tasks (e.g., cuBLAS, cuDNN).
  5. Debug and profile your GPU code using tools like cuda-gdb and Nsight.

Key Features

Course Curriculum

1. Overview of CUDA architecture and GPU programming.
2. Setting up CUDA Toolkit and development environment.
3. GPU vs. CPU computation models.
1. CUDA programming model: threads, blocks, grids.
2. Writing and launching basic CUDA programs.
3. Thread management and indexing.
1. Global, shared, local, and constant memory.
2. Efficient memory management and access patterns.
3. Memory coalescing and bank conflicts
1. Parallel algorithm design and decomposition.
2. Synchronization techniques: barriers, atomic operations.
3. Handling race conditions.
1. Identifying performance bottlenecks.
2. Optimizing memory access and thread execution.
3. Instruction-level optimization.
1. cuBLAS: Optimized linear algebra.
2. cuFFT: Fast Fourier Transform.
3. cuDNN: Deep learning acceleration.
4. Thrust: High-level parallel algorithms.
1. Using cuda-gdb for debugging.
2. Profiling with NVIDIA Nsight and Visual Profiler.
3. Analyzing memory usage and performance.
1. Multi-GPU programming and scaling.
2. CUDA Streams and Events for asynchronous execution.
3. Unified Memory and GPUDirect.
4. Using Tensor Cores for deep learning.
1. Real-world GPU-accelerated applications.
2. End-to-end application development.
3. Capstone project.
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Course Fees

Online Class Room Program

US $ 799.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 May 2026
  • Weekday Batch 01 Jun 2026
  • Weekend Batch 30 May 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support

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CUDA Certification

After completing the CUDA Programming Training and hands-on practical exercises, learners will receive a Course Completion Certificate from igmGuru. This certification validates your expertise in writing parallel programs using CUDA, optimizing GPU performance, managing memory efficiently, debugging and profiling GPU code, and utilizing advanced libraries like cuBLAS, cuFFT, and cuDNN. It also demonstrates your ability to scale applications with multi-GPU setups and integrate CUDA with machine learning and data processing workflows.

CUDA Certification

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