AMD ROCm Software: A Beginners Overview

Sep 18, 2024

Here at TensorWave, we are hardware nerds. We talk about hardware pretty much all the time. It’s in ...

Here at TensorWave, we are hardware nerds. We talk about hardware pretty much all the time. It’s in our blood and our DNA, and we provide our clients the best possible cloud AI hardware platform.

But computer hardware isn’t useful without software to run on it. We know that AI development is about two things: data and algorithms.

So, today we’re going to talk about software. In particular, this article presents an overview of AMD’s ROCm software. AMD are the kings of hardware, including the MI300X GPU that powers the TensorWave cloud. In addition, they provide an open-source suite of tools, drivers, and application programming interfaces (APIs) that make it easier to optimize the experience of AI development.

Why ROCm Software?

Why would you need such a thing?

A GPU is an extraordinary, complex device. The MI300X combines eight GPU “chiplets” with input-output circuitry and 192 GB of high-bandwidth memory in one package. Furthermore, the MI300X is scalable; multiple MI300X units can be combined to work together. Dividing an AI training task among all these parts so that the load is balanced on each unit to maximize efficiency is not something your average (or above-average) AI developer is eager to tackle. Among its other features, ROCm “hides” all of that so developers can focus on optimizing their algorithms.

Key features of ROCm include:

  1. HIP (Heterogeneous-Compute Interface for Portability): A C++ runtime API and kernel language that allows developers to write code that is portable between AMD and NVIDIA GPUs.
  2. MIOpen: A library for high-performance machine learning primitives, which provides optimized routines for deep learning frameworks.
  3. rocBLAS: A library for high-performance BLAS (Basic Linear Algebra Subprograms) operations.
  4. rocFFT: A library for fast Fourier transform operations.
  5. rocRAND: A library for random number generation.
  6. Thrust: A parallel algorithm library.
  7. rocm-smi: A tool for monitoring and managing system and GPU resources.

How ROCm Works

From an architecture standpoint, ROCm sits between the GPU hardware and the AI development framework; ROCm supports the most popular frameworks, including PyTorch, TensorFlow, JAX, ONNX, and more.

The components of ROCm include:

  • Device drivers and runtimes compatible with Linux distros such as RedHat and Ubuntu
  • A compiler, debugger, and other low-level development tools
  • AI-focused software libraries, such as MIOpen and MIVisionX

All of these components are open-source under MIT/BSD, Apache, or GPL licensing.

The ROCm ecosystem includes AMD Infinity Hub, a collection of pre-built software containers and deployment guides for both AI and high-performance computing (HPC) applications. In addition, AMD has joined the HuggingFace Hardware Partner Program to optimize the performance of transformers, LLMs, and other models on HuggingFace. Natural-language processing, speech recognition and synthesis, computer vision, and other AI applications all stand to benefit from this partnership.

Benefits of ROCm Software

How does ROCm benefit your development team? Here’s a sampling:

  • Ease of use: ROCm enables easy migration of existing AI code so that developers can take advantage of the platform without having to rewrite the existing code base.
  • Support for all levels of coding, from low-level kernels to GUI-based end-user applications.
  • Comprehensive developer toolkit, including profilers, debuggers, resource monitoring tools, container management tools, and more
  • Simplified model development: The HuggingFace partnership provides access to a wide range of open-source models so you don’t have to start every project from scratch.
  • Portability: Software developed with ROCm can be used on GPUs from other vendors or in a heterogeneous hardware environment.
  • Automatic hardware optimization: No matter how many MI300X GPUs you want to scale to, ROCm manages the distribution of tasks so your developers don’t have to.
  • Faster development cycles: Optimized hardware utilization means faster training and testing of even the largest AI models, so you can optimize both performance and inference accuracy.

Getting Started

How can you get started using ROCm software? AMD provides a number of developer resources on its Developer Central site. Developer Central includes everything you need to get started and make the most of ROCm, including:

  • Downloads
  • Documentation and technical guides
  • Training videos
  • Blogs and newsletters
  • Developer and community support forums
  • Registration portal for ROCm webinars
  • Webinar archive

AMD makes ROCm the best tool it can be, and it actively solicits feedback from the developer community for feature requests and bug reports.

ROCm and TensorWave

As the first-to-market and leading provider of AI cloud development services based on the AMD MI300X GPU, TensorWave  provides a unique opportunity to leverage the power and scalability of AMD’s flagship GPU. It helps you realize all the advantages of ROCm software—without having to purchase, deploy, configure, and manage the hardware in your own data center. The result is a high-quality, high-performance development platform with a low total cost of ownership.

And, unlike cloud AI services based on other GPUs, our service is available to you today to meet your AI goals now and in the future.

As an AMD shop, we’ve made it our business to understand and support the entire MI300X ecosystem, and this includes the ROCm software tools. Our consultants can help you get the most from our environment.
It’s an exciting time to be involved in AI development, and many businesses like yours are eager to take advantage of this new technology. To learn more about how TensorWave can help you achieve your AI transformation goals or to schedule a demo, contact TensorWave today.

About TensorWave

TensorWave is a cutting-edge cloud platform designed specifically for AI workloads. Offering AMD MI300X accelerators and a best-in-class inference engine, TensorWave is a top-choice for training, fine-tuning, and inference. Visit tensorwave.com to learn more.