The 25 Best HPC GPUs with Teraflop and Memory Information

High-Performance Computing (HPC) GPUs are specialized processors designed to tackle large-scale computations in fields like AI, scientific research, and data analysis.

I Which GPU fits your needs the most?

Teraflops measure how fast a GPU can perform trillions of calculations per second, while memory (VRAM) determines how much data the GPU can handle at once, crucial for tasks like simulations and 3D rendering.

This list highlights the 25 most popular HPC GPUs, covering teraflop performance (FP64 for precision tasks, FP16 for AI) and memory (VRAM). These GPUs are built for heavy computational tasks in AI, data analysis, and scientific simulations.

Single-GPU Cards:

Single-GPU cards like the NVIDIA A100 and AMD Instinct MI100 report total performance since they have one processing unit. These are ideal for AI training, deep learning, and scientific tasks that require powerful, high-precision computing.

Multi-GPU Cards:

Multi-GPU cards, such as the NVIDIA A16, feature multiple GPUs on a single card, suited for parallel processing. Here, performance is shown per GPU for handling multiple tasks simultaneously, common in virtualization and cloud workloads.

Memory (VRAM):

Memory capacity dictates how much data the GPU can handle. Cards with higher VRAM, such as 80GB HBM3 in the NVIDIA H100, can manage large datasets and complex AI models. HBM2e and HBM3 memory types, found in top GPUs, ensure fast data access, crucial for high-end HPC and AI applications.

This list provides key insights to help choose the right GPU based on performance and memory needs, ensuring optimal use for tasks like AI, scientific research, or parallel computing.