Amazon EC2 P4 Instances

Toyota Research Institute (TRI), founded in 2015, is working to develop automated driving, robotics, and other human amplification technology for Toyota.

“At TRI, we're working to build a future where everyone has the freedom to move,” said Mike Garrison, Technical Lead, Infrastructure Engineering at TRI. "The previous generation P3 instances helped us reduce our time to train machine learning models from days to hours and we are looking forward to utilizing P4d instances, as the additional GPU memory and more efficient float formats will allow our machine learning team to train with more complex models at an even faster speed."

"At TRI-AD, we're working to build a future where everyone has the freedom to move and explore with a focus on reducing vehicle injuries and fatalities using adaptive driving and smart city. Through the use of Amazon EC2 P4d instances, we were able to reduce our training time for object recognition by 40% compared to previous generation GPU instances without any modification to existing codes." said Junya Inada, Director of Automated Driving (Recognition) at TRI-AD.

Jack Yan, Senior Director of Infrastructure Engineering at TRI-AD said, "Through the use of Amazon EC2 P4d instances, we were able to instantly reduce our cost to train compared to previous generation GPU instances enabling us to increase the number of teams working on model training. The networking improvements in P4d allowed us to efficiently scale to dozens of instances which gave us significant agility to rapidly optimize, retrain, and deploy models in test cars or simulation environments for further testing."

GE Healthcare is a leading global medical technology and digital solutions innovator. GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications and services, supported by its Edison intelligence platform.

“At GE Healthcare, we provide clinicians with tools that help them aggregate data, apply AI and analytics to that data and uncover insights that improve patient outcomes, drive efficiency and eliminate errors,” said Karley Yoder, VP & GM, Artificial Intelligence. “Our medical imaging devices generate massive amounts of data that need to be processed by our data scientists. With previous GPU clusters, it would take days to train complex AI models, such as Progressive GANs, for simulations and view the results. Using the new P4d instances reduced processing time from days to hours. We saw two- to three-times greater speed on training models with various image sizes, while achieving better performance with increased batch size and higher productivity with a faster model development cycle.”

HEAVY.AI is a pioneer in accelerated analytics. The HEAVY.AI platform is used in business and government to find insights in data beyond the limits of mainstream analytics tools.

“At HEAVY.AI, we’re working to build a future where Data Science and Analytics converge to break down and fuse data silos. Customers are leveraging their massive amounts of data that may include location and time to build a full picture of not only what is happening, but when and where through granular visualization of spatial temporal data. Our technology enables seeing both the forest and the trees.” said (Ray Falcione), VP of US Public Sector at HEAVY.AI. “Through the use of Amazon EC2 P4d instances, we were able to reduce the cost to deploy our platform significantly compared to previous generation GPU instances thus enabling us to cost-effectively scale massive data sets. The networking improvements on A100 has increased our efficiencies in how we scale to billions of rows of data and enabled our customers to glean insights even faster.”

Zenotech Ltd is redefining engineering online through the use of HPC Clouds delivering on demand licensing models together with extreme performance benefits by leveraging GPUs.

“At Zenotech we are developing the tools to enable designers to create more efficient and environmentally friendly products. We work across industries and our tools provide greater product performance insight through the use of large scale simulation.” said Jamil Appa, Director of Zenotech. “The use of AWS P4d instances, enables us to run our simulations 3.5 times faster compared to the previous generation of GPUs. This speed up cuts our time to solve significantly allowing our customers to get designs to market faster or to do higher fidelity simulations than were previously possible.”

Aon is a leading global professional services firm providing a broad range of risk, retirement and health solutions. Aon PathWise is a GPU-based and scalable HPC risk management solution that insurers and re-insurers, banks, and pension funds can use to address today’s key challenges such as hedge strategy testing, regulatory and economic forecasting, and budgeting. 

“At PathWise Solutions Group LLC, our product allows insurance companies, reinsurers and pension funds to access next generation technology to rapidly solve today’s key insurance challenges such as machine learning, hedge strategy testing, regulatory and financial reporting, business planning and economic forecasting, and new product development and pricing” said Peter Phillips, President and CEO, PathWise Solutions Group. "Through the use of Amazon EC2 P4d instances we are able to deliver amazing improvements in speed for single and double precision calculations over previous generation GPU instances for the most demanding calculations, allowing new range of calculations and forecasting to be done by clients for the very first time. Speed matters,” says Phillips, “and we continue to deliver meaningful value and the latest technology to our customers thanks to the new instances from AWS.”

Comprised of radiology and AI experts, Rad AI builds products that maximize radiologist productivity, ultimately making healthcare more widely accessible and improving patient outcomes.

“At Rad AI, our mission is to increase access to and quality of healthcare, for everyone. With a focus on medical imaging workflow, Rad AI saves radiologists time, reduces burnout, and enhances accuracy,” said Doktor Gurson, Co-founder of Rad AI. “We use AI to automate radiology workflows and help streamline radiology reporting. With the new EC2 P4d instances, we’ve seen faster inference and the ability to train models 2.4x faster, with higher accuracy than on previous generation P3 instances. This allows faster, more accurate diagnosis, and greater access to high quality radiology services provided by our customers across the US.“

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