Training: HBeonLabs102-- Introduction to GPGPU using CUDA software

Fees: Contact us personally for the fee structure.  

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For Level "A", the student should be familiar with the concepts of C programming language. Although the parallel programming will be taught in the training in Level "A", but some exposure to it will help you grasp the concept quickly.   

Prerequisites: 

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Third year and final year students of Computer Science, Electronics &Comm Engineering, and Electronics & Instrumentation can enroll for this course. 

Target Audiences:

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Level"C" is the advance course and is mainly related to practical implementations. Level C is a hands-on course involving significant parallel programming on massive-core GPUs fundamentally CUDA compatible NVIDIA's GPU. Specifically we will be working on NIDS (Network Intrusion Detection System) acceleration on GPUs. This will require core knowledge of networking fundamentals as well CUDA programming skills.  

Level "B" discusses parallel programming concepts in detail giving specific focus on CUDA programming. Specifically you are exposed to the following special topics:Performance metrics - speedup, utilization, efficiency, scalability,Models of Parallel Computation: SIMD (Single Instruction Multiple Data), MIMD (Multiple Instruction Multiple Data), GPU Compute Architecture, CUDA, Memory organization in CUDA Multi-Core CPU programming, MPI, PVM, Performance evaluation and scalability.

Level"A" is an introductory course on parallel programming with about only20% of the time devoted for CUDA programming. This level does not require any parallel computing knowledge. Only a Data structures level course is required.

This course (HBCS102) is divided into three modules: Level "A" , Level "B" and Level "C", level C being the most advance course, comprising mainly of practical applications.

Course Overview:

Did you know, the graphics cards by NVIDIA that you use in your PC is actually a supercomputer!