GPU Programming

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GPU Programming

• Course Info
• Curriculum
• Instructors

Description

What the Specialization Covers

• Introduction to Concurrent Programming with GPUs: Covers core parallel programming principles, multi-threading in C and Python, and fundamental CPU vs. GPU hardware and software architectures.
• Introduction to Parallel Programming with CUDA: Focuses on hands-on CUDA development, writing custom CUDA kernels, and transforming standard CPU algorithms into parallel ones.
• CUDA at Scale for the Enterprise: Teaches multi-GPU and multi-CPU coordination, workload optimization, and enterprise-level scalability.
• CUDA Advanced Libraries: Explores high-performance computing and machine learning libraries like cuFFT, cuBLAS, and cuDNN.

Course Curriculum

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Instructors

Dhanvika Y

Experienced instructor passionate about teaching and sharing knowledge.