GPU Workstation for Finite Element Method Computing

The Finite Element Method (FEM) or Finite Element Analysis (FEA) is a numerical approach used to solve complex problems in engineering and physics. It breaks down large systems—such as structures, thermal fields, or fluid dynamics—into smaller, manageable parts called finite elements. Through this method, equations are established for each element, and a process known as finitary operation combines them to approximate solutions for the entire system. FEM is widely used in applications like structural analysis, heat transfer, and electromagnetics. The accuracy and efficiency of FEM are directly tied to computational power, as the larger and more intricate the system, the more finite elements must be processed.

FEM, despite its versatility, is computationally expensive. The division of a problem into finite elements leads to an explosion in the number of equations that need to be solved simultaneously. These equations often take the form of large, sparse matrices, requiring iterative methods or direct solvers to find solutions. Moreover, FEM computations must iterate multiple times to refine accuracy, particularly for nonlinear problems or dynamic systems. This demand for high precision, combined with the complexity of matrix operations, places enormous strain on traditional computing resources, leading to extended processing times even on powerful CPUs.

This is where GPUs (Graphics Processing Units) have dramatically transformed FEM computing. Unlike CPUs, which excel in handling a few tasks sequentially, GPUs are designed for massive parallelism. They consist of thousands of smaller, efficient cores that work simultaneously, making them ideal for tasks like matrix operations, which are central to FEM. GPUs accelerate linear algebra computations, such as matrix multiplication and decomposition, which are typically bottlenecks in FEM. As a result, what might take hours or days on a CPU can often be accomplished in a fraction of the time using GPUs. Furthermore, GPUs reduce latency in iterative processes, enabling faster convergence to accurate solutions. GPU-accelerated FEM not only cuts computation time but also allows for solving larger, more complex problems that were previously infeasible.

For professionals and researchers seeking a high-performance solution for FEM, a workstation equipped with 4 NVIDIA RTX 3090 GPUs and 2 powerful CPUs is an excellent choice. The RTX 3090 GPUs, with their large memory bandwidth and exceptional processing capabilities, handle the parallel computations required for FEM with ease. Meanwhile, the CPUs provide robust support for sequential tasks, pre-processing, and data management, ensuring a balanced workload. This configuration is particularly beneficial for FEM applications in fields like structural engineering or computational fluid dynamics, where the demand for precision and speed is paramount. The combined power of these GPUs and CPUs enables users to tackle complex simulations, reduce turnaround time, and push the boundaries of FEM research.

The introduction of GPUs into FEM computing has truly revolutionized the field, enabling faster, larger, and more accurate simulations. For those immersed in the challenges of FEM, leveraging GPU acceleration is not merely an option—it’s a game-changer.

Here we gave a GPU workstation solution for FEM/FEA.

• Processor: 2 x Xeon 8272 26 core 52 thread 2.6GHz
• RAM: 4 x 32GB DDR4 RECC server DRAM
• Storage: 1 x 960GB SSD
• GPU：4 x RTX3090 24GB turbine fan
• power supply: 2400W 80plus gold
• noise: ~75dB when full load

More customized workstation solution can be found here.