The explosion of silicon density in the past decade has resulted in increased massive compute capabilities of modern-day microprocessors in power-efficient packages. Processors supporting trillions of floating point operations (TFLOPS) are now becoming widely available in smaller form factors. Software paradigms have also been created to leverage the underlying hardware. In this talk, Mohammed Billoo will introduce Nvidia's CUDA framework, targeting a variant of the C programming language. Care needs to be taken when implementing applications using CUDA-C. The underlying hardware, specifically the memory architecture and layout, need to be considered to ensure that the final implementation is performant. Mohammed will cover the following topics in this talk:

• Architectural differences between GPUs and CPUs
• Relevant applications for GPUs
• CUDA-C overview and build process
• CUDA-C code structure

Mohammed will conclude the talk with a hands-on demonstration of an image processing algorithm implemented in CUDA-C on a Nvidia Jetson Nano development kit. He will compare the performance of the CUDA-C implementation on the GPU against a naive implementation on a CPU.