Benchmarking and performance optimization cloud solutions for HPC and AI workload.
We benchmark on the top-tier public cloud and neocloud platforms; you deploy on-prem with confidence.
Don’t invest millions in hardware just to run a few benchmarks. We give you instant access to performance data on large-scale cloud infrastructure—no procurement delays, no internal cluster limitations.
Stop projecting small-node results to 1,000-node systems. We run your customers’ actual workloads—at scale—on the latest chips, giving you hard performance data that wins RFPs and avoids costly acceptance penalties.
Focus on delivering value to your customers—we’ll handle multi-scenario performance testing across architectures, node counts, and clouds. We test more configs, so you can pitch the best one with confidence.
We benchmark industry-standard CAE workloads like OpenFOAM, ANSYS Fluent, Abaqus FEA, and Simcenter STAR-CCM+ to evaluate CPU/GPU scalability, solver performance, and memory efficiency. Ideal for automotive, aerospace, and manufacturing R&D.
We benchmark molecular dynamics, genomics, and protein folding codes to help you select the best architecture for bioinformatics and pharmaceutical research. These include; GROMACS, AlphaFold, and NAMD.
We benchmark tightly coupled models used in weather and climate prediction, like WRF, MPAS, NEMO, and CESM, as well as energy exploration including applications like SPECFEM3D and ResInsight—where MPI scaling, memory bandwidth, and I/O performance are critical.
We run ab initio, molecular dynamics, and electronic structure workloads, like LAMMPS, Quantum ESPRESSO, CP2K and VASP and to assess HPC/GPU efficiency for materials discovery, batteries, and nanotechnology.
We provide reproducible, architecture-agnostic synthetic benchmarks, like HPL, HPCG, STREAM, and OSU/IMB to measure raw compute, memory, and network performance—ideal for platform comparisons.
We benchmark deep learning training and inference workloads from LLM to MLPerf on GPUs and multi-node clusters to analyze scalability, GPU memory pressure, and cost/performance tradeoffs.
Need an HPC/AI workload benchmark fast? Tell us the app & scale—we’ll handle the rest.