Ansys recently integrated support for AMD Instinct™ MI200 and MI300 accelerators into Fluent, its Flagship CFD Solver, significantly enhancing simulation efficiency and power. With the Fluent GPU Solver, simulations that once took weeks or months can now be completed in hours or days.

AMD Instinct MI300X GPUs, advanced by one of the latest versions of open-source ROCm™  achieved impressive results in the MLPerf Inference v4.1 round, highlighting strength of the full-stack AMD inference platform. The initial submission focused on the widely recognized LLaMA2-70B model, known for its high performance and versatility. It demonstrated strong Gen AI inference performance against the NVIDIA H100, setting a strong precedent for the capabilities of AMD Instinct MI300X accelerators.

In the fast-paced world of artificial intelligence, Meta's new release, Llama 3.1, is a game-changer. Llama is an open-source advanced language model designed to understand and generate human-like text.

At AMD, we believe that AI is the most important thing to impact computing and technology in the past 50 years, and we remain dedicated to driving innovation and collaboration within the AI industry.   

Accelerated computing has taken the industry by storm—bringing dramatic changes to how software applications including AI and HPC are developed and tuned for maximum impact. GPGPU solutions, such as those from AMD, have been pivotal in enabling advances in both AI and HPC. In the AI space, their massive parallel processing capabilities have been critical in powering the AI revolution, by supporting key frameworks like PyTorch, TensorFlow, and JAX. At the same time, their raw computing power delivers the performance necessary to optimize HPC applications like GROMACS for molecular dynamics simulation, OpenFOAM for computational fluid dynamics, NAMD for molecular modeling, and Ansys Mechanical for computer-aided engineering. By providing a robust, unified software stack catering to both AI and traditional HPC workloads, these accelerated computing platforms are driving breakthroughs across scientific and industrial computing. The versatility of GPGPU architectures makes them the preferred solution for designing, developing, and deploying AI and HPC at scale. This unmatched capability is underpinned by robust software ecosystems, which include libraries and tools widely used in AI and machine learning. This comprehensive support makes the development and deployment process easier and more efficient. 

AMD continues to cornerstone the technology needed to enable the computational capabilities and possibilities of the world’s most powerful supercomputers across various sectors.