Gilthanis
[H]ard|DCer of the Year - 2014
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- Jan 29, 2006
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- 8,729
I added additional info in the first post about app_config changes due to them phasing out v7 work units and going to v8.
Follow along with the video below to see how to install our site as a web app on your home screen.
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Both petri33 and Oddbjornik have given the OK to release this more publicly so here it is!
This is the work sync mutex version of the famed Linux "special sauce" application. named V0.99. petri33 is the author of the bulk of the source code, but with the work sync mutex function added by Oddbjornik. I only compiled it . This app cuts out the load time of the next WU by pre-loading it while the first WU is running. This saves 1-5 seconds, sometimes more, per WU processing time. As such, it is slightly more productive overall than the regular v0.98 application.
Download here:
Requirements/notes:
1. You must be running Linux, I built/tested this on Ubuntu 18.04
2. You must have Nvidia driver version 440.xx+ installed, 440.36 is the latest driver at this time. this is a CUDA 10.2 requirement, not a Special app requirement. If you don't
3. As always, make sure the executable is set to allow execution, or you will generate compute errors due to lack of permissions.
4. This is the app ONLY. you need to add this to either the AIO package distributed by Tbar and edit the app_info.xml file appropriately, or add this to your boinc directory for a repository install (if you've added the special app previously to your repo install then you should already know where and how to put this)
5. For this to function as intended, you need to configure BOINC to run 2 WUs at a time on your GPU(s). you do this using an app_config.xml file like so:
<app_config>
<app>
<name>astropulse_v7</name>
<gpu_versions>
<gpu_usage>0.5</gpu_usage>
<cpu_usage>1.0</cpu_usage>
</gpu_versions>
</app>
<app>
<name>setiathome_v8</name>
<gpu_versions>
<gpu_usage>0.5</gpu_usage>
<cpu_usage>1.0</cpu_usage>
</gpu_versions>
</app>
</app_config>
*Note, If you run AP tasks on your GPU and you want them to be processed in FIFO fashion you need to also configure 2x WUs for AP tasks, or they will never run, or only run when they get close to timing out or you have no MB/v8 tasks to work on.
The one downside:
Since you are running double the number of WUs, you will use double the system memory resources, both on the CPU and GPU.
with 2 RTX 2080s running this:
system using ~4GB of system RAM
and ~3GB per GPU.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.36 Driver Version: 440.36 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2080 On | 00000000:01:00.0 On | N/A |
| 65% 70C P2 193W / 200W | 3254MiB / 7979MiB | 98% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce RTX 2080 On | 00000000:03:00.0 Off | N/A |
| 50% 64C P2 198W / 200W | 2832MiB / 7982MiB | 99% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 970 G /usr/lib/xorg/Xorg 240MiB |
| 0 1109 G /usr/bin/gnome-shell 195MiB |
| 0 1704 C ./keepP2 111MiB |
| 0 19733 C ...p_V0.99b1p3_x86_64-pc-linux-gnu_cuda102 1351MiB |
| 0 19793 C ...p_V0.99b1p3_x86_64-pc-linux-gnu_cuda102 1351MiB |
| 1 970 G /usr/lib/xorg/Xorg 6MiB |
| 1 1705 C ./keepP2 111MiB |
| 1 19692 C ...p_V0.99b1p3_x86_64-pc-linux-gnu_cuda102 1351MiB |
| 1 19759 C ...p_V0.99b1p3_x86_64-pc-linux-gnu_cuda102 1351MiB |
+-----------------------------------------------------------------------------+