Hi Frank, I tried both 2.6 and 2.5-stable. 2.6  showed marginal improvements 
at-least for my workload (improvement of ~1K for 70% read, 30% random workload).

-Deepak

________________________________
From: Frank Filz <ffilz...@mindspring.com>
Sent: Tuesday, February 13, 2018 7:26:50 AM
To: Deepak Jagtap; nfs-ganesha-devel@lists.sourceforge.net
Subject: RE: [Nfs-ganesha-devel] nfs ganesha vs nfs kernel performance


What version are you running? Significant improvements have been made in V2.6 
(which is close to being tagged V2.6.0).



Frank



From: Deepak Jagtap [mailto:deepak.jag...@maxta.com]
Sent: Monday, February 12, 2018 4:01 PM
To: nfs-ganesha-devel@lists.sourceforge.net
Subject: [Nfs-ganesha-devel] nfs ganesha vs nfs kernel performance



Hey Guys,



I ran few performance tests to compare nfs gansha and nfs kernel server and 
noticed significant difference.



Please find my test result:



SSD formated with EXT3 exported using nfs ganesha  : ~18K IOPS    Avg latency: 
~8ms       Throughput: ~60MBPS

same directory exported using nfs kernel server:             ~75K IOPS    Avg 
latency: ~0.8ms    Throughput: ~300MBPS



nfs kernel and nfs ganesha both of them are configured with 128 worker threads. 
nfs ganesha is configured with VFS FSAL.



Am I missing something major in nfs ganesha config or this is expected behavior.

Appreciate any inputs as how the performance can be improved for nfs ganesha.





Please find following ganesha config file that I am using:



NFS_Core_Param

{

        Nb_Worker = 128 ;

}



EXPORT

{

    # Export Id (mandatory, each EXPORT must have a unique Export_Id)

   Export_Id = 77;

   # Exported path (mandatory)

   Path = /host/test;

   Protocols = 3;

   # Pseudo Path (required for NFS v4)

   Pseudo = /host/test;

   # Required for access (default is None)

   # Could use CLIENT blocks instead

   Access_Type = RW;

   # Exporting FSAL

   FSAL {

        Name = VFS;

   }

   CLIENT

   {

        Clients = *;

        Squash = None;

        Access_Type = RW;

   }

}







Thanks & Regards,

Deepak

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