Recommended Scientific Workstations
At Puget Systems, we do a LOT of testing. We believe that computers should be a pleasure to purchase and own. They should get your work done, and not be a hindrance. To do that, they need to be the right hardware for the job. When it comes to workstations for scientific computing, that first means understanding the unique demands of computationally intensive algorithms. Thankfully we have an expert in this field on staff: Dr. Don Kinghorn. He spends a lot of time testing out the capabilities of new computer hardware, writing informational posts in his HPC Blog, and assisting our consulting team with customer questions. He has helped tailor the science workstation configurations below for various aspects of research and data processing using high performance processors, multiple GPUs, or a mix of both.
Select your workflow:
Scientific Computing covers many fields, including ML/AI and data-analysis within those domains. Our workstations are built for applications demanding high-performance numerical computation. GPU acceleration is also a serious consideration!
Machine Learning / AI
Our Machine Learning / AI workstation configurations are single CPU, multi-GPU, and optimized for model training with NVIDIA GPU acceleration. These are great platforms for working with frameworks like TensorFlow, PyTorch, MXNet, etc.
Our Data Science workstations provide lots of memory, lots of storage, many-core CPUs, and big-memory GPUs. ETL and preprocessing are handled well with these systems, including end-to-end workflows with model training and analysis using very large data sets.