Cuda Vst Plugins Average ratng: 7,6/10 9799 votes
Have an account? sign in register
All Plug-ins, Hosts, Apps & Soundware in the KVR Product Database on One Page. It functions as a VST Plugin, an Audio Units Plugin and an RTAS Plugin. Product: Filtrate: Developer: LiquidSonics: Price (MSRP). 64-bit VST and AU on Mac and PC. Updated: I discovered the Acustica Audio Nebula plugins which can use CUDA. Looks like much of the net chatter about these plugins is about excessive latency, possibly attributable to CUDA, and the fact that using CUDA doesn't actually increase the overall max track or plugin count.
- •Applications•Where it's
used - •Hardware•Specs and
reviews - •Programming•Algorithms and
techniques - •Resources•Source codes,
tutorial, books, etc. - •Tools•GPU
services
Realtime Computation of a VST Audio Effect Plugin on the Graphics Processor
HAW Hamburg, University of Applied Sciences, Hamburg, Germany
The Third International Conference on Creative Content Technologies, CONTENT 2011, 2011
@inproceedings{fohl2011realtime,
title={Realtime Computation of a VST Audio Effect Plugin on the Graphics Processor},
how to record audio on garageband ipad author={Fohl, W. and Dessecker, J.},
booktitle={CONTENT 2011, The Third International Conference on Creative Content Technologies},
pages={58–62},
year={2011}
Free vst eq with presets. }
Download (PDF)ViewSource
A plugin system for GPGPU real time audio effect calculation on the graphics processing unit of the computer system is presented. The prototype application is the rendering of mono audio material with head-related transfer functions (HRTFs) to create the impression of a sound source located in a certain direction relative to the listener’s head. The virtual source location can be controlled in realtime. Since HRTFs are measured only for certain incident angles, a interpolation for intermediate angles has to be performed in realtime. Plugins are implemented using the VST software development kit offered by Steinberg Media Technologies. Two GPU processing frameworks for a NVIDIA graphics processor were evaluated: CUDA and OpenCL. The overall processing speed can be increased by the factor 2.2 with the GPGPU modules. When calculating the FIR filter outputs by fast convolution on the GPU, the processing speed can even be increased by the factor ten.
Rating: 5.0/5. From 1 vote.
Related
Recent source codes
ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction
waLBerla: (widely applicable Lattice Boltzmann from Erlangen), massively parallel framework for multi physics applications
NaturalCC: A Toolkit to Naturalize the Source Code Corpus
Systolic CNN
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning
EasyPBR: A Lightweight Physically-Based Renderer
Telamon: a framework to find good combinations of optimization for computational kernels on GPUs
Evaluating the Performance Portability of Contemporary SYCL Implementations
BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs
cuSZ: CUDA-Based Error-Bounded Lossy Compressor for Scientific Data
Most viewed papers (last 30 days)
Featured events
December
The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020
November
The Fifth International Workshop on GPU Computing and AI (GCA), 2020
January
2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021
December
Cuda Vst Plugins Downloads
International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020
December
Cuda Vst Plugins Download
International Conference on Wireless Networks and Embedded Systems (ICWNES’20), 2020