Green Video Collaboration Technology
Employing sustainable practices in software engineering
Committed to green code
At Cordoniq, we use eco-friendly practices to build our video collaboration platform. From day one, we’ve fully utilized the processing capabilities of devices with clean, native code concepts. This includes writing SIMD-based instructions for Arm32 and Arm64 platforms and NEON targets.
We also take advantage of every internal instruction that we can utilize on the chipsets within low-end devices like Smart TVs. The result is a solution that can run in an energy-efficient manner with minimal jitter and a smooth, real-time experience.
Gamification from the ground up
Cordoniq is also the only video collaboration platform designed with gamification, at its core. Which means our software offloads the heavy lifting of rendering videos, shared content and media to the graphics processing unit (GPU) rather than relying solely on the central processing unit (CPU) and memory. This produces smoother frames per second, and higher video resolution.
Delivering earth-friendly results
Combining lean code with gamification decreases the number of computing cycles needed on both cloud data center modules and handheld devices by fully leveraging their low-level capabilities.
As a result, devices achieve better utilization rates. This significantly reduces energy consumption and promotes carbon neutrality
Elevating user experiences
Our approach allows the user interface (UI) to display more video windows and live collaboration elements simultaneously, giving you a superior interactive and immersive user experience. This is true, even on older devices with limited power, battery life and capability. (e.g. older Android™ phones).
Realizing efficiencies –
data centers & the cloud
In the data center and in the cloud, web services and backend logic that utilizes off-the-shelf and layers of open source technology can quickly become energy inefficient. General purpose web technologies are often built to meet the needs of many diverse solutions. This introduces inefficiencies in design that impact the overall energy consumption.
When building cloud-based data center solutions, best practice involves tailoring the solution to the exact requirements and reducing unnecessary computing cycles, both in terms of processor load, memory consumption and heat generation in the data center. This requires a periodic reevaluation of the tools being used and the implementation approach as well as code refactoring to accomplish tasks more efficiently using less computing cycles.