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HenriquesLab / NanoJ-SRRF

Super-resolution radial fluctuations (SRRF)
GNU General Public License v3.0
22 stars 2 forks source link

GPU Processing Issue after latest driver updates #4

Open Sveeggen opened 4 years ago

Sveeggen commented 4 years ago

Apologies in advance, my coding experience is virtually nonexistent, but I can no longer get SRRF to run.

The error:

EM com.amd.aparapi.internal.kernel.KernelRunner executeOpenCL WARNING: ### CL exec seems to have failed. Trying to revert to Java ###

The last time I used SRRF, I was able to blaze through a .nji file in under 30 seconds, but now it's claiming to require an hour at 0 FPS. Based on my reading, it sounds like the program is no longer able to utilize my GPU? This is frustrating because this plug-in was giving us great data with zero issues prior to now!

Since I last used it about a month ago, I believe there have been updates to FIJI, Java, and my NVIDIA drivers. As a habit I updated these all automatically, but now I can't find old files to roll back to and prove it's the new drivers causing issues. Regarding the NVIDIA drivers, I have tried both the gaming and studio drivers to no avail.

My computer info:

Operating System: Windows 10 Home 64-bit Card name: NVIDIA GeForce GTX 1060 Card driver: 441.20 (11/12/2019) Java Version: 8 Update 231 FIJI Version: 1.52r SRRF Version: 1.14 Stable 1

Any ideas? This really is an amazing plug-in that our lab would hate to not be able to use.

Edit: Update

I have also checked OpenCL in ImageJ and tested that OpenCL is able to detect my graphics card as successfully test it with Mandelbrot. So ImageJ and OpenCL can recognize my graphics card but for some reason SRRF can no longer use OpenCL?

XarlesSta commented 4 years ago

Dear Sveeggen, were you able to resolve this issue? I am in the same rabbit hole and I have tried every driver there is. Any of them works. I know my Fiji is also communicating with my GPU. For example, CLIJ works but NanoJ does not.

Sveeggen commented 4 years ago

Dear Sveeggen, were you able to resolve this issue? I am in the same rabbit hole and I have tried every driver there is. Any of them works. I know my Fiji is also communicating with my GPU. For example, CLIJ works but NanoJ does not.

Sadly I am still having trouble. We have ended up using an older computer to run it - though it takes around 3 minutes per image, that's at least manageable. I worry there needs to be an update or something to work with newer computers, but I have no idea how to go about that.

joaomamede commented 4 years ago

Congrats Dr. Henriques in starting your lab at IGC!!

I have the same error and message about openCL: EM com.amd.aparapi.internal.kernel.KernelRunner executeOpenCL WARNING: ### CL exec seems to have failed. Trying to revert to Java ###

I tested the openCL with the NanoJ-core test for openCL and the animation and test runs properly. When I try to run NanoJ-SRRF I have the same error as you.

I have tried in my Lenovo Legion Y540 with a Geforce RTX 2060 and in my lab's microscope computer HP 4 with a Geforce Quadro .

I have tried in windows 10 and in Ubuntu 20.04. Operating Systems : Ubuntu 20.04 + Windows 10 Home 64-bit + Windows 10 Pro 64-bits Card name: NVIDIA GeForce RTX 2060 / Nvidia Quadro Card driver: 440.82-0ubuntu0~0.20.04.1 (Ubuntu) + 451.22 (windows) FIJI Version: 1.52p Java Running: 1.8.0_172(64-bits) NanoJ-Core: 2.1RC1 SRRF Version: 1.14 Stable1\ I have CUDA libraries installed in both my Ubuntu 20.04 and W10 in my lenovo.

From my Ubuntu install NanoJ-Core tests. " Running Device Tests NVIDIA Corporation_GPU Identity of device used: - NVIDIA Corporation_GPU global:589824 local:(derived)1024 Execution mode=GPU Executed at 748.0FPS Best Device: - NVIDIA Corporation_GPU "

I know that in linux the CUDA components changed recently. Would this be connected to it? My camera is 2048x2044 so using CPU in a 100 frame image is basically 1h+. I could use CPU in a small ROI sucessfully.

XarlesSta commented 4 years ago

This config works for me:

  1. Open NVIDIA Control Panel --> Manage 3D settings.
  2. Go to Global Settings tab.
  3. In the setting window, change the 'Power Management Mode' to 'Prefer Maximum Performance'.
  4. Also check below settings too, • Power management mode – prefer maximum performance • Ambient Occlusion – Off • Triple buffering – off • Threaded optimization - ON • Vertical Sync – Adaptive
  5. Click on Save and restart the Computer.
  6. Run the program and check.

Please let me know if it works for you.

joaomamede commented 4 years ago

Did not help me (windows). Still drops to CPU mode. Linux doesn't have any of those options in nvidia-settings.

joaomamede commented 4 years ago

Okay. I think it's something to do with the 440+ drivers. As I got my laptop from my new workplace today I tested it right away, and I made a lucky mistake of installing old drivers.

It did work. System:

Red hat enterprise Linux 8 Quadro T2000 NVIDIA-SMI 430.26 Driver Version: 430.26 CUDA Version: 10.2

we are actually getting an EMCCD with SRRF, but I'd like to also do SRRF with my CMOS as well. Any way we can make the plugin more verbose to see if there's a library problem or something like that?

I'm installing the most recent 440 right now to see if I can reproduce the error.

EDIT1: after installing 440.100 it fails with the opencl error. I also tried 450 beta from the rhel cuda repository and that resulted in crashing imageJ

Outputs from the app nvidia-smi tool in linux (to show versions) Works: NVIDIA-SMI 430.26 Driver Version: 430.26 CUDA Version: 10.2

Fail: NVIDIA-SMI 440.100 Driver Version: 440.100 CUDA Version: 10.2 NVIDIA-SMI 450.36.06 Driver Version: 450.36.06 CUDA Version: 11.0

EDIT2: Windows 10 64bits with Quadro RTX 4000 Works : 423.28-quadro-desktop-notebook Fail: 436.30-quadro-desktop-notebook ; 451.48-quadro-desktop-notebook

DSbioimaging commented 4 years ago

I am also experiencing this problem on a 2070S under Windows 10

+-----------------------------------------------------------------------------+ | NVIDIA-SMI 451.82 Driver Version: 451.82 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+

cilia-etc commented 4 years ago

I was having the same error (...CL exec seems to have failed...) and I was able to resolve it on a Windows 10 machine with an NVIDIA Quadro P4000. To resolve the error, I reverted back to the original drivers from March, 16 2018. The driver version according to the Windows Device Manager is: 23.21.13.9125.

To revert back to these drivers, I went in through: Device Manager -> Update Driver ->Browse for Driver -> Let me pick..

The earliest driver was from March 16, 2018 (presumably from when the system was built). So, I picked that driver and restarted the system.

SRRF is now working at GPU speeds after doing the above.

I am not the most savvy GPU person and so I don't know the difference between the Windows Device Manager version numbers and the 450, 440, 430 numbers listed on the Nvidia downloads page. However, I was not able to get SRRF to work with either the 440 or 430 driver installers that I downloaded from the Nvidia webpage. It was only when I went in through Device Manager that SRRF started working again.

I hope this helps someone.

DSbioimaging commented 3 years ago

I was having the same error (...CL exec seems to have failed...) and I was able to resolve it on a Windows 10 machine with an NVIDIA Quadro P4000. To resolve the error, I reverted back to the original drivers from March, 16 2018. The driver version according to the Windows Device Manager is: 23.21.13.9125.

To revert back to these drivers, I went in through: Device Manager -> Update Driver ->Browse for Driver -> Let me pick..

The earliest driver was from March 16, 2018 (presumably from when the system was built). So, I picked that driver and restarted the system.

SRRF is now working at GPU speeds after doing the above.

I am not the most savvy GPU person and so I don't know the difference between the Windows Device Manager version numbers and the 450, 440, 430 numbers listed on the Nvidia downloads page. However, I was not able to get SRRF to work with either the 440 or 430 driver installers that I downloaded from the Nvidia webpage. It was only when I went in through Device Manager that SRRF started working again.

I hope this helps someone.

Thank you for replying, unfortunately the newer graphic card models (like my 2070S and the upcoming 3XXX models) do not have the option of rolling back to older drivers, the earliest driver supporting my graphic card happens to have a higher version number than the one you are using. I will try to post on Nvidia forums but given the love they have previously shown for OpenCL, I am less than hopeful that they will do anything about it.

Repacking the project with a newer Aparapi version could fix the issue, but I lack the skills to do so. The whole project feels abandoned (Especially the Bitbucket dead links).

joaomamede commented 3 years ago

I tried to open the Nano-Updater.jar, and just replace the naparapi .so files inside to see if that would work. Doing so breaks NanoJ.

The package that needs the update is in NanoJ-core (updater). The .dll and .so files are in that github, and I believe they come from aparapi-jni

joaomamede commented 3 years ago

I'm trying to get this recompiled with more recent aparapi. The reason why we can't just change the libraries in updater is that before it was "import com.amd.aparapi" and with more recent versions it's: "import com.aparapi"

I am trying to recompile everything and I spent a fair amount of time finding maven libraries. I got stuck here (when compiling the module NanoJ-Core it can't find libraries within its own src directory.

I'm a python guy, so I have never done this. Any tips? image

joaomamede commented 3 years ago

I managed to make a jar with the latest aparapi.

I have this problem in Fiji. If it fixed the nvidia driver issue,I will share the jars and try to fork the updates I did to nanoj-core into github.

There was a problem with the class org.apache.bcel.Repository which can be found here:
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/jars/xalan-2.7.2.jar
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/plugins/NanoJ-Core.jar
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/plugins/NanoJ-Updater.jar

WARNING: multiple locations found!
java.lang.NoSuchMethodError: org.apache.bcel.Repository.lookupClass(Ljava/lang/Class;)Lorg/apache/bcel/classfile/JavaClass;
    at com.aparapi.internal.model.ClassModel.parse(ClassModel.java:2842)
    at com.aparapi.internal.model.ClassModel.<init>(ClassModel.java:187)
    at com.aparapi.internal.model.ClassModel.createClassModelInternal(ClassModel.java:676)
    at com.aparapi.internal.model.ClassModel.access$300(ClassModel.java:88)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:671)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:668)
    at com.aparapi.internal.model.ValueCache.computeIfAbsent(ValueCache.java:50)
    at com.aparapi.internal.model.ClassModel.createClassModel(ClassModel.java:682)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalInner(KernelRunner.java:1474)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalOuter(KernelRunner.java:1383)
    at com.aparapi.internal.kernel.KernelRunner.execute(KernelRunner.java:1374)
    at com.aparapi.Kernel.execute(Kernel.java:2897)
    at com.aparapi.Kernel.execute(Kernel.java:2854)
    at com.aparapi.Kernel.execute(Kernel.java:2829)
    at nanoj.updater.java.InstallNanoJDependencies.<init>(InstallNanoJDependencies.java:36)
    at nanoj.core.java.gui._BaseDialog_.<clinit>(_BaseDialog_.java:37)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at ij.IJ.runUserPlugIn(IJ.java:233)
    at ij.IJ.runPlugIn(IJ.java:198)
    at ij.Executer.runCommand(Executer.java:150)
    at ij.Executer.run(Executer.java:68)
    at java.lang.Thread.run(Thread.java:748)

[ERROR] java.lang.NoSuchMethodException: Could not find method org.apache.bcel.Repository.lookupClass(Ljava/lang/Class;)Lorg/apache/bcel/classfile/JavaClass;
There was a problem with the class org.apache.bcel.Repository which can be found here:
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/jars/xalan-2.7.2.jar
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/plugins/NanoJ-Core.jar
/home/jmamede/Downloads/fiji-linux64(1)/Fiji.app/plugins/NanoJ-Updater.jar

WARNING: multiple locations found!
java.lang.NoSuchMethodError: org.apache.bcel.Repository.lookupClass(Ljava/lang/Class;)Lorg/apache/bcel/classfile/JavaClass;
    at com.aparapi.internal.model.ClassModel.parse(ClassModel.java:2842)
    at com.aparapi.internal.model.ClassModel.<init>(ClassModel.java:187)
    at com.aparapi.internal.model.ClassModel.createClassModelInternal(ClassModel.java:676)
    at com.aparapi.internal.model.ClassModel.access$300(ClassModel.java:88)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:671)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:668)
    at com.aparapi.internal.model.ValueCache.computeIfAbsent(ValueCache.java:50)
    at com.aparapi.internal.model.ClassModel.createClassModel(ClassModel.java:682)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalInner(KernelRunner.java:1474)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalOuter(KernelRunner.java:1383)
    at com.aparapi.internal.kernel.KernelRunner.execute(KernelRunner.java:1374)
    at com.aparapi.Kernel.execute(Kernel.java:2897)
    at com.aparapi.Kernel.execute(Kernel.java:2854)
    at com.aparapi.Kernel.execute(Kernel.java:2829)
    at nanoj.updater.java.InstallNanoJDependencies.<init>(InstallNanoJDependencies.java:36)
    at nanoj.core.java.gui._BaseDialog_.<clinit>(_BaseDialog_.java:37)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at ij.IJ.runUserPlugIn(IJ.java:233)
    at ij.IJ.runPlugIn(IJ.java:198)
    at ij.Executer.runCommand(Executer.java:150)
    at ij.Executer.run(Executer.java:68)
    at java.lang.Thread.run(Thread.java:748)

    at com.aparapi.internal.model.ClassModel.parse(ClassModel.java:2842)
    at com.aparapi.internal.model.ClassModel.<init>(ClassModel.java:187)
    at com.aparapi.internal.model.ClassModel.createClassModelInternal(ClassModel.java:676)
    at com.aparapi.internal.model.ClassModel.access$300(ClassModel.java:88)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:671)
    at com.aparapi.internal.model.ClassModel$4.compute(ClassModel.java:668)
    at com.aparapi.internal.model.ValueCache.computeIfAbsent(ValueCache.java:50)
    at com.aparapi.internal.model.ClassModel.createClassModel(ClassModel.java:682)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalInner(KernelRunner.java:1474)
    at com.aparapi.internal.kernel.KernelRunner.executeInternalOuter(KernelRunner.java:1383)
    at com.aparapi.internal.kernel.KernelRunner.execute(KernelRunner.java:1374)
    at com.aparapi.Kernel.execute(Kernel.java:2897)
    at com.aparapi.Kernel.execute(Kernel.java:2854)
    at com.aparapi.Kernel.execute(Kernel.java:2829)
    at nanoj.updater.java.InstallNanoJDependencies.<init>(InstallNanoJDependencies.java:36)
    at nanoj.core.java.gui._BaseDialog_.<clinit>(_BaseDialog_.java:37)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at ij.IJ.runUserPlugIn(IJ.java:233)
    at ij.IJ.runPlugIn(IJ.java:198)
    at ij.Executer.runCommand(Executer.java:150)
    at ij.Executer.run(Executer.java:68)
    at java.lang.Thread.run(Thread.java:748)
pawlowska commented 3 years ago

@joaomamede have you managed to get a working version for the plugin? I belong to this unlucky group whose drivers are too new for the official version

joaomamede commented 3 years ago

I did not. I compiled it but i have never done Java or fiji plug-ins. Some of the libs should come from fiji, some from maven and things got messed up and it does not run.

joaomamede commented 3 years ago

Old bitbucket stuff can be found here:

https://web.archive.org/web/20200624140819/https://bitbucket.org/rhenriqueslab/nanoj-srrf/wiki/Getting%20set%20up%20with%20SRRF

https://web.archive.org/web/20200622021429/https://bitbucket.org/rhenriqueslab/nanoj-core/wiki/Home

Something interesting is, that nano-core always picks the best card. We can probably unload the nvidia module if we have a prime laptop and run in the Intel HD, but we can't select Intel HD because the internal nanoj-core code picks the best card and only list that one. (talking about linux btw)

DSbioimaging commented 3 years ago

Old bitbucket stuff can be found here:

https://web.archive.org/web/20200624140819/https://bitbucket.org/rhenriqueslab/nanoj-srrf/wiki/Getting%20set%20up%20with%20SRRF

https://web.archive.org/web/20200622021429/https://bitbucket.org/rhenriqueslab/nanoj-core/wiki/Home

Something interesting is, that nano-core always picks the best card. We can probably unload the nvidia module if we have a prime laptop and run in the Intel HD, but we can't select Intel HD because the internal nanoj-core code picks the best card and only list that one. (talking about linux btw)

Thank you so much for the link! After so much trial and error, I finally understand much better what each setting is doing and that several settings are absolutely not useful for my setup (High density non blinking emitters). I tried browsing the old repo through that website looking for the Squirrel documentation to further confirm data from sub diffraction beads, but it was not cached... Has anybody managed to get a reply by contacting the authors? I tried writing directly to Prof. Henriques and Dr. Culley but alas, they did not get back to me.

Regarding your linux issue, if you are running Ubuntu, you should be able to switch off the Nvidia card by using nvidia-prime.

Do you think that editing the jar file and the relative classes inside would be easier than compiling the source?

joaomamede commented 3 years ago

I tried, but the classes are compiled in binary code in the plugin in fiji, so it has to be recompiled.

I managed to compile this github version without any modifications, only by adding the jars from fiji in the libraries declarations.

image

Somehow the resources with the libaparapi.so are not being inserted into the jars. I need to find out how to do it, if anyone has tips on how to do it, please let me know.

joaomamede commented 3 years ago

Okay I got it to compile and run on Fiji:

With IntelliJ idea File > New > Project from version control File > Project Settings > set SDK to 1.8

Set each Module to each folder (one for NanoJ_Core one for NanoJ_updater) . NanoJ-core has NanoJ_updater as dependency image

Add Libraries and point to jars in your Fiji/Fiji.apps/jars directory (see picture in the previous post)

Create Artifacts from the module (and add the respective resource files into them) image

Build Create Artifacts and the Jars should be created and run.

I'll try with the most aparapi version (and change all the com.amd.aparapi to com.aparapi hoping it will solve the problem). Cross your fingers for us!

joaomamede commented 3 years ago

It's not an easy swap. The classes got a re-write in newer aparapi com example com.aparapi.Kernel doesn't exist, com.aparapi.util.Kernel . I think the best I'll try to do is to make nanoJ-core to ignore my nvidia and try to run from my integrated intel. (with the module blacklisted it leads to crashes, as the nvidia opencl libraries are still installed).

(Fiji Is Just) ImageJ 2.1.0/1.53c; Java 1.8.0_172 [64-bit]; Linux 4.18.0-240.8.1.el8_3.x86_64; 329MB of 37163MB (<1%)

java.lang.NoClassDefFoundError: com/aparapi/Kernel
    at nanoj.core.java.gui._BaseDialog_.<clinit>(_BaseDialog_.java:37)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at ij.IJ.runUserPlugIn(IJ.java:233)
    at ij.IJ.runPlugIn(IJ.java:198)
    at ij.Executer.runCommand(Executer.java:150)
    at ij.Executer.run(Executer.java:68)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ClassNotFoundException: com.aparapi.Kernel
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    ... 11 more
DSbioimaging commented 3 years ago

It's not an easy swap. The classes got a re-write in newer aparapi com example com.aparapi.Kernel doesn't exist, com.aparapi.util.Kernel . I think the best I'll try to do is to make nanoJ-core to ignore my nvidia and try to run from my integrated intel. (with the module blacklisted it leads to crashes, as the nvidia opencl libraries are still installed).

(Fiji Is Just) ImageJ 2.1.0/1.53c; Java 1.8.0_172 [64-bit]; Linux 4.18.0-240.8.1.el8_3.x86_64; 329MB of 37163MB (<1%)

java.lang.NoClassDefFoundError: com/aparapi/Kernel
  at nanoj.core.java.gui._BaseDialog_.<clinit>(_BaseDialog_.java:37)
  at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
  at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
  at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
  at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
  at java.lang.Class.newInstance(Class.java:442)
  at ij.IJ.runUserPlugIn(IJ.java:233)
  at ij.IJ.runPlugIn(IJ.java:198)
  at ij.Executer.runCommand(Executer.java:150)
  at ij.Executer.run(Executer.java:68)
  at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ClassNotFoundException: com.aparapi.Kernel
  at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
  at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
  at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
  at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
  ... 11 more

Thanks for having tried! Your test was definitely worth a shot to see if a simple swap could help us figure this out. I will try out of curiosity on my windows laptop with an intel i7 8550 and a geforce mx150, I have distant memories of switching between integrated and discreet GPU when the plugin came out. It's not directly relevant to your case, but it could help with isolating the issue between NanoJ and the OS side of the equation.

I want to also report that few day ago, the GPU suddenly decided to work, there was no warning and I could definitely see a speed up in the execution speed. Sadly I did not manage to ever reproduce what triggered that state, the only thing I had open at the time was youtube in firefox. I thought that maybe the hardware video decoding somehow kept the GPU in an active state so I also tried to start SRRF while an opencl benchmark (luxmark) was running in the background without success.

I am also thinking to buy a recent-ish amd gpu to use exclusively with SRRF.

DSbioimaging commented 3 years ago

Since you are running linux, you might want to give POCL a go. http://portablecl.org/docs/html/

If I understood how this work, after the installation, it should come up as a choice in the CL-Device menu in nanoj or could be selected by an ICD-loader (https://manpages.ubuntu.com/manpages/xenial/man7/libOpenCL.7.html). It supports nvidia opencl acceleration through cuda so it might be a roundabout way to restore GPU acceleration.

joaomamede commented 3 years ago

my opencl works fine with both intel-neo and nvidia-cl. It's all of nanoJ-core that doesn't support recent intel GPU (neo), it doesn't even detect it, and nano-srrf specifically, >435 nvidia drivers. With the same OS and my old old old old claptop with old intel opencl libs (not Neo), there's no problem whatsoever.