# Core AMD ROCm™ Software Application Development - Associate Certification

**URL:** <https://www.artofsm.art/t/core-amd-rocm-software-application-development-associate-certification/22854>\
**Category:** Content Creators\
**Tags:** gpu, amd-developer-centra, machine-learning, amd\
**Created:** [18 August 2026 17:04 UTC](https://www.artofsm.art/t/core-amd-rocm-software-application-development-associate-certification/22854 "2026-08-18T17:04:10Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![merefield](https://www.artofsm.art/user_avatar/www.artofsm.art/merefield/32/74_2.png) [@merefield](https://www.artofsm.art/u/merefield)\
**Post date:** [18 August 2026 17:04 UTC](https://www.artofsm.art/t/core-amd-rocm-software-application-development-associate-certification/22854/1 "2026-08-18T17:04:10Z")

</div>

[![](https://www.artofsm.art/uploads/default/original/3X/0/c/0c62d37031673aa75babca01ff1bdd9972d3711a.jpeg "Core AMD ROCm™ Software Application Development - Associate Certification") ](https://www.youtube.com/watch?v=Ckp4eGPZVmE)

The ROCm Certified Associate course provides a practical introduction to AMD’s open AI software stack, focusing on developing, optimizing, and deploying AI and HPC applications on AMD Instinct GPUs using the HIP programming model. It covers foundational GPU concepts, ROCm software layers, HIP programming, and performance optimization techniques, equipping learners with hands-on skills to write efficient GPU applications and integrate ROCm with popular AI frameworks.

---

<div class="post-metadata">

**Author:** ![merefield](https://www.artofsm.art/user_avatar/www.artofsm.art/merefield/32/74_2.png) [@merefield](https://www.artofsm.art/u/merefield)\
**Post date:** [18 August 2026 17:24 UTC](https://www.artofsm.art/t/core-amd-rocm-software-application-development-associate-certification/22854/3 "2026-08-18T17:24:29Z")

</div>

The ROCm Certified Associate course offers a comprehensive introduction to AMD’s open AI software stack, designed for both newcomers and those seeking to validate their skills. It emphasizes hands-on labs and practical exercises to help learners develop, optimize, and deploy AI and HPC applications on AMD Instinct GPUs using ROCm software and the HIP programming model. This approach ensures participants gain real-world expertise rather than just theoretical knowledge.

The course begins with foundational GPU concepts and an introduction to ROCm, AMD’s open software stack for accelerated computing. It also covers HIP, a portable C++ programming model that facilitates GPU application development and CUDA code porting. Participants will explore the architecture of AMD Instinct accelerators, including compute units, SIMD hardware, matrix engines, and the memory hierarchy, gaining a practical understanding of how GPU code executes through grids, blocks, threads, and wavefronts.

Moving up the software stack, the course examines ROCm’s optimized compute libraries and AI frameworks such as PyTorch, Triton, RCCL, and vLLM. These technologies leverage ROCm to support various AI workflows, including training, inference, distributed execution, and production serving. This section bridges the gap between hardware understanding and software application, demonstrating how ROCm integrates with popular AI tools.

The course then delves into practical HIP programming, guiding learners through the structure of a complete GPU program. Key topics include memory management, data movement, kernel launches, error checking, timing, and the process of porting CUDA code to HIP. This hands-on programming experience equips participants with the skills needed to write efficient and correct GPU applications on AMD platforms.

Finally, the course focuses on performance optimization techniques. Using profiling and roofline analysis, learners identify bottlenecks and apply strategies such as coalesced memory access, LDS tiling, block-size tuning, and reduced-precision computation to enhance performance. By the end of the series, participants will have a solid foundation in AMD GPU systems, enabling them to select appropriate ROCm software layers, develop or port GPU code, and evaluate both correctness and performance effectively.

## Useful Links

- [AMD ROCm Certified Associate Course](https://developer.amd.com/rocm-certified/) — Directly substantiates and enables action on the main claim about the ROCm Certified Associate course content and learning outcomes.
- [AMD ROCm Official Developer Resources](https://www.amd.com/en/developer.html) — Supports practical development and learning as described in the course summary.
- [AMD ROCm Developer Community](https://devcommunity.amd.com/) — Enables engagement and support for learners and developers using ROCm as described in the video.