GPU Audio has announced the arrival of macOS support for its FIR Convolution Reverb, an early-access plugin which uses Impulse Responses (IRs) to accurately replicate the tonal reflections and sonic characteristics of any acoustic space.

Being traditionally one of the most processor intensive plugin effects out there, this FIR Convolver is the perfect audio tool to try out GPU Audio’s unique processing technology.

Producers and musicians know that CPU spikes and inconsistent performance can really dampen a session, so the ability to offload this processing to devices already present in your machine is a huge innovation for the audio industry, and a great opportunity for musicians to get back in the flow. Graphics Cards offer vastly superior and scalable performance gains over CPUs, with the capability to seamlessly process audio in parallel, while having multiple plugin instances running at ultra low latencies.

This new release paves the way for the next generation of pro audio plugins on Apple M1 and M2 devices, with all of the benefits that brings, including Live Machine Learning and A.I. processing – something which Graphics Cards specialise in and excel at. GPU Audio processing is going to put untapped power in your hands, so the demands of creating modern immersive experiences through the likes of Spatial Audio can stop pushing your CPU to its limits and start boosting your creative energy.

FIR Convolution Reverb is now available to download for both Windows and macOS at no charge. Users can share feedback on performance and features at the GPU Audio website and at its Discord community.

An SDK (Software Development Kit) for third party developers is due for release in early 2023; delivering collaborative and independent plugins harnessing the power of your GPU for high fidelity audio experiences.

Mach1 will be releasing the first 3rd party plugin in conjunction with GPU Audio, in addition other high-profile connections due to be announced and more welcomed. Developers can sign up for the SDK.

More information: GPU Audio