Colleagues, in the “Multicore and GPGPU Programming” program you will understand the fundamentals of multi-threaded programming and its applications in multicore systems. Develop shared memory programs in OpenMP and distributed programming using MPI. Gain a foundational understanding of GPGPU architecture and the CUDA programming model. Gain high-demand skills involving Distributed Computing, System Programming, C and C++, OS Process Management, Hardware Architecture, Scalability, Data Sharing, Program Development, Algorithm, Performance Tuning, Memory Management, Computer Architecture, Microarchitecture, and Performance Testing. The course delves into designing shared memory data structures and introduces advanced synchronisation concepts, including lazy synchronisation, crucial for scalable and efficient concurrent applications. Additionally, students will explore the architecture and programming model of General-Purpose Graphics Processing Units (GPGPUs) and learn CUDA programming to leverage GPU parallelism for compute-intensive tasks. By the end of the course, students will be adept in optimising multi-threaded and many-core applications, balancing workload across CPUs and GPUs to achieve high throughput and efficient resource utilisation. This course is essential for those aiming to develop expertise in high-performance computing and parallel programming for modern multi-core and GPU-based systems.
Enroll today (teams and executives are welcome): https://imp.i384100.net/LKZ95a
Recommended Reading:
1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)
2 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle)
3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)
Much success in your AI career, AI Academy (please subscribe and share with you colleagues)

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