HPE develops a complete set of AI solutions
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HPE has announced that it is working to remove barriers for companies to easily build and train machine learning models at scale, to deliver value faster, with the new HPE Machine Learning Solution Development System. This new system, designed specifically for AI, is a comprehensive solution that encompasses a software platform, computing, accelerators and communications to develop and train AI models more accurately, faster, and at scale.
The HPE Machine Learning Development System is the result of investment made by HPE with the acquisition of IA Determined to combine its robust Machine Learning (ML) platform, now known as HPE Machine Learning Development Environment, with its AI and HPC solutions. With HPE’s new ML development system, users can accelerate the time it takes to get value from their models, and start getting results from building and training those models, reducing time from weeks and months to just a few days.
HPE also announced today that Aleph Alpha, a German AI startup, has adopted the HPE ML Development System to train its multimodal AI, including Natural Language Processing (NLP) and machine vision. Combining text and image processing in five languages with near-human-like context understanding, the models push the boundaries of modern AI for all sorts of innovative language- and image-based use cases, such as assistants AI for complex text creation, high-level summaries and comprehension, searching for highly specific information in hundreds of documents, and leveraging specialized knowledge in a conversational context.
The HPE Machine Learning Development System is the result of the investment made by HPE with the acquisition of IA Determined
By adopting HPE’s ML development system, Aleph Alpha has gotten its system up and running efficiently in record time, combining and monitoring hundreds of GPUs.
“We are seeing amazing efficiency and performance of over 150 teraflops when using the HPE Machine Learning Development System. The system was quickly set up and we started training our models in hours instead of weeks. Being able to run these massive workloads, combined with our ongoing research, relying on an integrated solution for deployment and monitoring, made all the difference,” said Jonas Andrulis, Founder and CEO of Aleph Alpha.
“Enterprises are looking to incorporate AI and ML to differentiate their products and services, but often face the complexity of setting up the infrastructure needed to build and train accurate AI models at scale,” said Justin Hotard, Executive Vice President and general manager of HPC and AI, at HPE. “The HPE ML Development System combines our comprehensive end-to-end HPC solutions for deep learning with our innovative ML software platform in a single system, providing a high-performance, out-of-the-box solution that accelerates the time it takes to get value and results with AI.”
Harness the full potential of AI with Machine Learning
Organizations have yet to reach maturity in their AI infrastructure, which, according to IDC, is the most significant and expensive investment required for companies that want to accelerate their experimentation or prototyping phase to develop AI products and services. Typically, adopting AI infrastructure to support scale model development and training requires a complex, multi-step process that involves purchasing, configuring and managing an ecosystem of parallel processing software, as well as an infrastructure that encompasses processing, storage, interconnection, and specialized accelerators.
The HPE ML Development System helps companies avoid the high complexity associated with adopting the AI infrastructure, to the offer the only solution that combines software, specialized computing with accelerators, networks, and services, enabling enterprises to immediately begin building and efficiently training optimized ML models, at scale.
Get accurate models to faster time to value with the HPE ML Development System
The system also helps improve model accuracy faster with state-of-the-art distributed training, automated hyperparameter optimization, and neural architecture search, which are key to ML algorithms.
The HPE Machine Learning Development System offers optimized compute, accelerated compute, and interconnect, which are key performance factors for efficiently scaling models for a mix of workloads, starting from a small configuration of 32 GPUs up to a configuration larger than 256 GPU. In a small configuration of 32 GPUs, the HPE ML Development System delivers approximately 90% scaling efficiency for workloads such as natural language processing (NLP) and computer vision. Additionally, based on internal testing, the HPE ML Development System with 32 GPUs delivers up to 5.7 times the speed for a PLN workload compared to solutions containing the same 32 GPUs but with one less interconnect. efficient.
The HPE ML Development System is offered as an integrated solution that provides a fully installed and preconfigured AI infrastructure for turnkey model development and training at scale. As part of our offering, HPE Pointnext Services will provide on-site software installation and configuration, allowing users to immediately deploy and train ML models for faster, more accurate insights from their data.
The HPE ML Development System is offered from a basic configuration as a small building block, with options to grow and increase the configuration. The base configuration has these elements:
- Optimized AI infrastructure using the system HPE Apollo 6500 Gen10 to provide massive and specialized compute capabilities for training and optimizing AI models, starting with 8 NVIDIA A100 80GB GPUs for accelerated computing.
- Precise, centralized monitoring and management arrangement for optimal performance with HPE Performance Cluster Management a system management software solution.
- Tools to monitor and manage system components using HPE ProLiant DL325 servers and Ethernet switch Aruba CX-6300 of 1 Gb.
