Course

Syllabus

Contents:

1. Data Transfer from UART through DMA
2. Group Scan using ADC
3. Fault Signaling Protocol implementation using Safety Management Unit
4. CPU Trap recognition and handling
5. Shared and Global Memory Implementation using Cuda
6. Analysis of Cuda Thread and Block using GPU
7. Implementation of Wrap Divergence using Cuda
8. Legacy code conversion to multicore environment
9. QNX configuration and application development using QNX
10. Process and thread creation, management, and synchronization using QNX
11. Implementation of IPC methods using message passing in QNX
12. Building and deploying QNX boot/OS images.

Text Books / References

Reference (s)

1. AURIX™ TC21x/TC22x/TC23x Family 32-Bit Single-Chip Microcontroller, User Manual, Infineon Technologies AG, 2015
2. Jaegeun Han, Bharatkumar Sharma, Learn CUDA Programming A beginner’s guide to GPU programming and parallel computing with CUDA 10.x and C/C++, Packt Publishing, 2019
3. CUDA CUDA C++ Programming Guide, NVDIA, 2024
4. QNX Neutrino RTOS User’s Guide, QNX Software Systems

Course Objectives

• To implement peripheral configuration in an advanced microcontroller
• To implement concepts of multicore programming
• To implement programming experiments using Graphical Processing Unit
• To implement Task Management using QNX

Course Outcomes:

• CO01: understand the configuration of peripherals in an advanced microcontroller
• CO02: apply multicore programming techniques
• CO03: analyze utilization of GPU resources
• CO04: implement CUDA programs in GPU hardware
• CO05: implement QNX processes and task management

CO-PO Mapping:

Skills Acquired: Configuration of peripherals of an advanced processor, CUDA programming using GPU, QNX implementation