I have a requirement to use a freeware linux user mode library for data processing.
The input data is purely in kernel space and we are finding it very difficult to port
whole freeware community based project to build under linux kernel build system !
So normally the requirement is to make a callback from kernel to user mode,
call user mode lib and let it process input data
return back to kernel mode and signal the consumer.
Is it possible to achieve kernel to user mode callback ?
If it's not possible, then I have another idea to create a user mode thread making kernel calls (ioctl),
which initially blocked, being signalled when there is sufficient data. Come back to user mode,
process data in user mode, make an ioctl call, switch to kernel mode,
But the second scheme will be costlier and include 2 context switch and also difficult
to adapt in our enviornment.
Your suggestions will be very helpful.
|Speed Up Your Web Site with Varnish||Jun 19, 2013|
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
- Speed Up Your Web Site with Varnish
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Linux Systems Administrator
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- Android's Limits
- Weechat, Irssi's Little Brother
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?