How to Install and Uninstall libzita-convolver4 Package on openSuSE Tumbleweed

Last updated: November 07,2024

1. Install "libzita-convolver4" package

In this section, we are going to explain the necessary steps to install libzita-convolver4 on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                libzita-convolver4
            
                    
    
    Copied

2. Uninstall "libzita-convolver4" package

Please follow the steps below to uninstall libzita-convolver4 on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                libzita-convolver4
            
                    
    
    Copied

3. Information about the libzita-convolver4 package on openSuSE Tumbleweed

Information for package libzita-convolver4:
-------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libzita-convolver4
Version : 4.0.3-1.18
Arch : x86_64
Vendor : openSUSE
Installed Size : 68.5 KiB
Installed : No
Status : not installed
Source package : zita-convolver-4.0.3-1.18.src
Upstream URL : https://kokkinizita.linuxaudio.org/linuxaudio/
Summary : A partitioned convolution engine library
Description :
Convolution engine based on FFT convolution and using non-uniform partition
sizes: small ones at the start of the IR and building up to the most efficient
size further on. It can perform zero-delay processing with moderate CPU load.
Main features:
* Any matrix of convolutions between up to up 64 inputs and 64 outputs, as
long as your CPU(s) can handle it.
* Allows trading off CPU load to processing delay, and remains efficient even
when configured for zero delay.
* Sparse and diagonal matrices are handled as efficiently as dense ones.
No CPU cycles or memory resources are wasted on empty cells in the matrix,
nor on empty partitions if IRs are of different length.