GPU ACceleration for CAE
Supercharge CAE Simulations with GPU Acceleration
Harness the performance of next-generation GPUs to tackle the most demanding Computer-Aided Engineering (CAE) challenges by leveraging the power of parallel computing. By shifting computationally intensive tasks from CPUs to GPUs, Rescale unlocks order-of-magnitude improvements in performance and cost efficiency for a wide range of applications.
Business Impact
Drive Speed & Efficiency in Engineering and Scientific R&D
Achieve Significant Cost-Efficiency
Realize substantial cost savings by leveraging GPUs, just as Boom Supersonic estimated 30x greater cost-efficiency through the use of GPUs for computational fluid dynamics.
Optimize Performance and Reduce Costs
Achieve faster results and lower expenses by optimizing GPU utilization, just as SLB (Schlumberger) achieved 12.9x faster results and 30.1x reduced cost with GPU optimization for coupled CFD-DEM simulations.
Accelerate Scientific Workloads
Expedite R&D outcomes by accessing and optimizing with GPUs, just as AzothBio achieved 2x faster results in molecular dynamics and drug discovery through GPU utilization.
GPU-OPtimized CAE
Harness the Power of
Compute Parallelization
GPUs significantly enhance high performance computing (HPC) by accelerating computationally intensive workloads. Originally designed for graphics rendering, GPUs excel at parallel processing, making them ideal for simulations, data analytics, and AI/ML. Rescale makes this power accessible for both CAE and other computationally intensive tasks, delivering substantial performance gains.
VISUALIZATION & VIrtual Desktops
Visualize Large-Scale
Simulations in Real Time
Rescale’s Elastic Cloud Workstations, virtual desktops tailored to the needs of HPC and AI workflows, provide engineers with the ability to interact with complex models and simulations in real time. Access to the latest GPUs on Rescale is crucial for pre-processing, post-processing, and interactive simulation, enabling faster analysis and better-informed decisions.
To learn more about GPU acceleration, contact us for a demo tailored to your needs.
New GPU Hardware Adoption
Stay at the Cutting Edge of
HPC and AI Compute Power
Rescale provides access to the latest GPU architectures—including those from NVIDIA, such as the B200—along with NVIDIA’s CUDA-X libraries and Omniverse platform for advanced engineering use cases. This ensures that users can leverage the most advanced hardware for their CAE workflows, maximizing performance and staying competitive.
Specialty Clouds for GPU Capacity
Access GPUs at Any Scale
Rescale offers scalable access to GPU resources across major cloud providers and specialized cloud solutions such as CoreWeave. To ensure availability of GPUs as demand increases, Rescale also provides reserved capacity purchasing options.
CFD GPU Benchmark
Ansys Fluent Accelerated
Ansys Fluent, a widely used Computational Fluid Dynamics (CFD) solver in industries like aerospace, automotive, and energy, benefits significantly from GPU acceleration. Fluent’s GPU solver delivers a substantial performance increase compared to its CPU-based counterpart, as demonstrated by external aerodynamics benchmarks where lower solve times indicate superior performance.
CFD GPU Benchmark
Siemens Star-CCM+
Siemens Simcenter STAR-CCM+ is a comprehensive multiphysics simulation tool used to analyze fluid flow, heat transfer, and structural mechanics in complex geometries. Its GPU-accelerated solver delivers significant performance gains over traditional CPU-based approaches, as shown in benchmark comparisons where lower costs and solve times highlight improvements in both speed and energy efficiency.
Optical Benchmark
Ansys Speos
Ansys Speos is used to predict illumination and optical performance, reducing the need for physical prototypes while improving design efficiency. The GPU-accelerated solver in Ansys Speos delivers improved performance compared to CPU-based solutions, speeding up the design and analysis of optical systems.
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