OnScale recently released its a solver-as-a-service platform called OnScale Cloud.
The platform addresses demand for computer-aided engineering (CAE) and cloud computing resources to solve engineering challenges in areas such as, Internet of Things (IoT), Industrial Internet of Things (IIoT), sensors, biomedical and smart car industries, according to Ian Campbell, OnScale’s chief executive officer.
“The CAE/HPC space is ripe for disruption because yesterday’s systems are too expensive and cumbersome to solve tomorrow’s engineering problems,” Campbell said. “Our platform eliminates the risk associated with sequential trial-and-error physical prototyping, reduces design cycles from months to weeks or even days, and delivers unequaled computing performance that easily scales to meet ever-changing CAE workloads.”
The company initially targeting underserved market verticals, worth $4 billion, with heavy demand for advanced computer-aided engineering and high-performance computing (HPC), Campbell said. OnScale will initially focus on the following market segments:
5G – RF Filters and RF switches for 5G smartphones and base stations.
IoT and IIoT – Microphone arrays for Alexa-style IoT devices, motion and gesture sensors, biometric and fingerprint sensors and industrial sensor systems.
BioMed – Advanced therapies, targeted treatment planning and consumer ultrasound.
Driverless Car Systems – Driverless car sensing technologies like 3D ultrasound for object classification, driver and passenger monitoring.
The company’s SaaS platform combines CAE multi-physics solvers with a scalable cloud HPC platform. OnScale gives individual engineers, small engineering design teams, and multinational engineering firms cost effective computational power, agility, and scalability through a pay-as-you-go subscription model, Campbell said.
OnScale charges engineers for actual solver time, measured in core-hours. For example, a solve that requires a 16-core HPC and 30 minutes to solve would consume eight core hours. Engineers can use as many HPC instances as they like to solve massive optimization studies in parallel. This means engineers who use OnScale Cloud and the companies they work for don’t buy new CAE software licenses, pay for maintenance and support, procure expensive HPC hardware, or wait for IT to deploy and maintain CAE systems, Campbell added.
OnScale Cloud is offered in three monthly subscriptions, all with a bundle of core-hours included, for discounted, on-demand pricing:
Free: Any engineer can begin using OnScale for free and receive ten core-hours, per month without commitment. Ten core-hours is sufficient to perform many simulations of simple devices. Additional on-demand core-hours can be purchased with a credit card for $10 per core-hour.
Professional: The Professional OnScale Cloud subscription is $300 per month and includes 50 core-hours, which opens up simulation of more complicated designs and parametric design studies. Additional on-demand core-hours can be purchased for $9 per core-hour at the Professional subscription level.
Team: The Team OnScale Cloud subscription is $1,000 per month and includes 200 core-hours, enough for a small engineering team to optimize next-generation devices. Additional on-demand core-hours can be purchased for $7 per core-hour at the Team subscription level.
In addition to these subscription levels, OnScale also provides discounts for annual subscriptions and flexible subscription programs for small, medium, and large enterprises, Campbell said.
“OnScale was built for engineers, by engineers,” he said. “We’ve experienced the restrictive nature of legacy CAE tools ourselves, so we designed OnScale tools to help engineers at Fortune 100 companies and startups alike remove cost and compute constraints.”
In March, the company emerged from its stealth position and announced $3 million in strategic seed funding. Campbell founded the company along with Robbie Banks, vice president of product development, and Gerry Harvey, vice president of engineering. OnScale is a spin-off of the company Thornton Tomasetti.