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GPU Compute Platforms for AI and Deep Learning

Full-Stack Partner helping your team transform data into intelligence.

Designing, implementing, and deploying Artificial Intelligence (AI) and Deep Learning (DL) infrastructure can be time consuming and daunting. The complexity of high-performance computing compared with traditional data center applications requires demanding workloads and a technology partner with expertise in infrastructure design.

We Can Help

With extensive compute, storage, and network experience coupled with our strategic sourcing capabilities and deployment knowledge, we can get you up and running in weeks vs. months. We have specialized training in designing for specific workload applications across academia, research, gaming, manufacturing, oil gas, retail, life sciences, and financial modeling.

Rapid Time to Value in Weeks vs. Months

We’ll help you avoid hardware complexity, engineering scarcity, and platform dependency.

Lower Your Costs and Inefficient Manual Interventions

Be able to deploy any cloud workload faster.

Reduce Risk and Dependency

Get started with product specific, workload optimized and tested, pre-built AI & ML models.

We Make It Easy

We already have the process and knowledge to bring all the different pieces of node set-up in a quick and easy process. With over 30 years of experience in the compute industry, we can source products where and when you need them when others simply can’t.

We also understand that there is a lot more than simply procuring products. You must identify what is available, map it to the workload, verify that it will work, identify a reliable and consistent supply, build when needed, and in many cases, deploy it around the world. Next, you need to ensure that it stays up and running. We do all of this for you.

We simplify this process even further with our full-stack integrated and automated approach to connect all the intermediary pieces to provide you with your desired business outcome.

Our Process

We partner with you as an extension of your team to understand your application, workload, and requirements to ensure you get what you need, when you need it. We build a flexible framework that allows us to evolve as the market or your needs change. Furthermore, we also continue to manage your product after the deployment to make sure that your product stays up-to-date even when other components are going end of life.

Discover

Design

Develop

Deploy

Support

Work with our team of Solution Architects, Developers, DevOps, Product Engineers, and Product Owners.

Our Solution Architects will collect the requirements and make sure that the best options are considered among the copious server classes available in the market. They are experts not only on the latest technology, but also on what is available and how to use it.

Our developers work tirelessly to ensure that you get the full-stack most relevant for your application and that it is seamlessly integrated into our full solution.

Our DevOps engineers are obsessed with automating medial tasks, helping to ensure that everything is done for you, whether that is IT Infrastructure, Cloud, or Container & Orchestration management. So that you can configure and deploy infrastructure quickly.

The Product Engineers and Product Owners are responsible for developing the product and keeping it operating for the lifecycle of the product.

Product Solutions

AI Workstations

AI Servers

Cluster Infrastructure

NVIDIA

Our end-to-end AI Performance-Optimized Framework and SDK’s That we automate using Neural Stack.

Neural Stack is a collection of frameworks, applications, and AI models enabling GPU-accelerated computational

AI Tools Included in our collection: 

Deep Learning Frameworks:

Updated monthly, PyTorch and TensorFlow containers are optimized for GPU acceleration, and contain a validated set of libraries that enable and optimize GPU performance. These containers also contain software for accelerating ETL, training, and inference.

RAPIDS:

Accelerates end-to-end data science and analytics pipelines entirely on GPUs.

TensorRT:

Takes a trained network and produces a highly optimized runtime engine that performs inference for that network.

TAO:

A python-based AI toolkit for taking purpose-built pre-trained AI models and customizing them with your own data. Add all 3 TAO containers in the entities tab.

Triton:

An open-source software to deploy trained AI models from any framework, on any GPU- or CPU-based infrastructure in the cloud, data center, or embedded devices.

DeepStream:

This SDK delivers a complete streaming analytics toolkit for AI based video and image understanding and multi-sensor processing.

RIVA:

A GPU-accelerated SDK for building speech applications that are customized for your use case and deliver real-time performance. Include RIVA Clients and RIVIA Speech skills.

Have Questions? Get in Touch!

Please complete the form and submit your preferred contact information. One of our expert team members will reach out to discuss your needs asap. We look forward to working with you.