Up to
5x
application speed-up
Memory vulnerabilities
100%
eliminated
Code changes required
Zero
Hassle-free acceleration
Ground breaking
10 years
research & development
The web is built on managed languages, primarily Python/Django, C#, Java and JavaScript. Though inefficient, these languages enable rapid and continual development of the application platform; their speed penalties are compensated by deploying additional server real estate on demand, at substantial cost. VyperCore technology reduces the footprint needed for a given volume of usage, substantially reducing TCO via capex and opex minimisation.
Financial analysts can now deploy sophisticated applications written in managed languages, still running in real-time with VyperCore acceleration technology. These applications will play a pivotal role in real-time predictive analytics, fraud detection, and risk management. The application acceleration allows the swift processing and analysis of vast datasets enabling financial institutions to make faster, more accurately informed, data-driven decisions.
In products with demanding power requirements such as smart watches and mobile phones, vendors are increasingly utilising accelerated computing of managed language applications to offload specific tasks to dedicated accelerators. Integrating VyperCore technology will enable the efficient releasing of resources from the main application's processor, enabling optimised battery life and power efficiency.
Security and power efficiency are the key drivers in always-on, always-connected Edge and IoT markets. The ability to utilise VyperCore secure accelerated computing will bring fast, easy to program managed-language applications into this highly resource constrained traditionally deeply embedded microcontroller market space.
The ability to rapidly deploy managed-language applications to process complex medical data using sophisticated algorithms up to five times faster enables the early detection and treatment of diseases, resulting in faster and more accurate clinical decisions that optimise patient outcomes. In the field of life sciences, VyperCore accelerated computing will allow faster data processing, eg of genetic sequences, to make more significant strides, and provide valuable insights into human biology. This knowledge is instrumental in advancing personalised medicine, tailoring treatments to individual patients based on their genetic makeup.
Artificial Intelligence applications are mainly run on general-purpose CPUs, using frameworks such as PyTorch that are written around managed languages. VyperCore will substantially accelerate ML inference on these frameworks. Separately, GenAI is delivering huge amounts of AI-written code into production deployments, often without human intervention to optimise it. This code will be readily accelerable with VyperCore technology.
