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Hi everyone, I was wondering if I could permanently disable iGPU folding in the F@H client. I don't fold 24/7 on my gaming rig so every time I restart the system it automatically starts folding a new work unit on my iGPU and I can't figure out a way to prevent it. I tried setting it to "Finish" the WU with the idea that it remains finished and doesn't fold anymore on it, but it always restarts once I turn on the system. Removing the iGPU folding slot also doesn't work as it always re-adds the slot when the system reboots. Thanks!

Why Linux: It will run well on older hardware that can be re purposed for a dedicated folding machine. You can disable automatic updates. Though Core22 has narrowed the performance gap between Windows and Linux anecdotal evidence still suggest there is a slight performance increase Folding on Linux. I have found it to be more stable than Windows with months of up-time. YMMV Why Ubuntu: It is well supported by a large Community and the Long Term Support (LTS) version is supported by Canonical until April 2027. Prerequisites: Pretty much any 2GHz or faster processor with a minimum of 2-3GB DDR3 and a PCIe 2 x16 slot should work. If you’re not running DHCP on your router you’ll need an available IP Address, and to note your Subnet Mask and Gateway Address. NVidia GTX or RTX GPU (AMD GPUs are NOT covered here yet, but if anyone wants to contribute please do so) OS Install (Ubuntu Desktop 22.04.2 LTS): This is the LTS Desktop version. More adventurous types may want to consider installing the LTS Server version for a less cluttered install. There are several other guides on how to setup a Linux Folding Rig (see the References Section at the end) Note: Ubuntu 19 removed support for Python2 so FAHControl will not work without some effort Download Ubuntu 22.04.2 LTS Desktop ISO File Burn the ISO to a USB Flash Drive using Rufus or similar tool Boot from the USB key and start the install For US English just accept the defaults Partition the whole disk as a single “Root” partition, don’t bother creating a separate swap partition. Select a “Minimal” install and to “Add 3rd-Party Drivers” Use the default Gnome Desktop (GDM3) for now, it can be changed later. To use “CoolBits” to Over or Under-Clock or change Fan speed control you will need to disable the newer “Wayland” X Server in favor of the classic Xorg Server (more later) OS Configuration: Graphics Drivers: OpenCL: Folding Client: Configuring X-Windows and GPU: System Administration 101: Advanced Topics: References: IT87 Kernel Module (All Gigabyte, and some Asus, Motherboards): Kernel.org: IT87 Kernel Module Default Supported Chips Phoronix: IT87 Linux Driver For Supporting Many Motherboard Sensors Is Facing Death Leve1Techs: I patched the IT87 (Temperature monitoring) driver, need some help testing it GitHub: Read-Only Archive of Guenter Roeck's Experimental IT87 Driver Ubuntu 18.04 LTS Install Guide here

Summary A method for implementing scheduling Distributed Computing (DC) tasks to take advantage of Time-of-Use (ToU) Electricity rates. Introduction Once you start running multiple Central Processing Units (CPUs) and Graphics Processing Units (GPUs) working on Distributed Computing (DC) tasks the energy consumed can become large and Utility power bills a significant burden. Many Utility power providers offer Time of Use (ToU) rates where electricity is priced most expensively at “On-Peak” times, more expensively at “Mid-Peak” times and least expensively at “Off-Peak” times. Depending on your goals and finances it may be convenient to suspend DC tasks during more expensive ToU periods and resume them during less expensive ToU periods. For example, my electricity provider in Eastern Ontario, Canada, defines ToU rates for summer (May 1st through October 31st) and winter (November 1st through April 30th) weekdays: Season Start Time Period Cost $/kWh Summer 07:00 Mid-Peak 0.102 Summer 11:00 On-Peak 0.151 Summer 17:00 Mid-Peak 0.102 Summer 19:00 Off-Peak 0.074 Winter 07:00 On-Peak 0.151 Winter 11:00 Mid-Peak 0.102 Winter 17:00 On-Peak 0.151 Winter 19:00 Off-Peak 0.074 As can be seen the electricity rate more than doubles during the On-Peak period compared to Off-Peak and is 39% more expensive during Mid-Peak periods. The rationale for the periods is that the “baseload” power during off-peak periods is supplied from always on-line Nuclear and Hydro-electric generation and during Peak usage more expensive generation using Natural Gas is employed. During summer the On-Peak period corresponds to the hottest period of the day and was likely established to encourage consumers to reduce set-points on Air Conditioning (A/C) to conserve electricity. The Winter On-Peak rates appear to target times when households are waking or arriving home from work and so appear to be encouraging use of high power devices such as drying machines and stoves earlier and later in the day. BOINC The Berkeley Open Infrastructure for Network Computing (BOINC) client supports suspending applications and no penalty is incurred for suspending then resuming a task. The BOINC Manager application includes functionality for scheduling when during the day tasks should run: Note, however, that you can only schedule one period of activity per day and so may be unsuitable for more complex use cases. To accommodate needing to schedule more than one BOINC suspend/resume cycle in a day we can leverage the boinccmd application which can be used to send commands to a locally attached BOINC client or a remote client by specifying its IP Address and, optionally, a password. The BOINC client must first be configured to allow Remote Procedure Calls (RPCs) on the target client, the source of the RPC call must be specified and, optionally, a password. Linux/MacOS The examples used here are for Linux (Ubuntu 22.04) but can be used on a Mac. There is no command to suspend or resume all BOINC applications running on a host but the running applications can be enumerated using the tool and the results used to suspend or resume all running applications. For a locally attached client the syntax is: for url in $(boinccmd --get_project_status | sed -n 's/\s*master URL: //p'); do boinccmd --project ${url} suspend; done For a remote client the syntax is: for url in $(boinccmd –-host <IP> [--passwd <Password>] --get_project_status | sed -n 's/\s*master URL: //p'); do boinccmd –-host <IP> [--passwd <Password>] --project ${url} suspend; done On a local host the code can be placed in a script and launched at appropriate times using the cron utility. Create the script: sudo nano ~/all_boinc_tou.sh Adding: #!/bin/bash for url in $(/usr/bin/boinccmd --get_project_status | sed -n 's/\s*master URL: //p'); do /usr/bin/boinccmd --project ${url} $1; done Type <Ctrl>+x to exit the editor saving the file. Make the script executable: sudo chmod +x ~/all_boinc_tou.sh Edit the root crontab: sudo crontab –e appending: # use /bin/bash to run commands, instead of the default /bin/sh SHELL=/bin/bash # Time of day BOINC # Summer: May 1st - Oct 31st # Mid-Peak 07:00 - 11:00 00 07 * * 1-5 /root/all_boinc_tou.sh suspend # On-Peak 11:00-17:00 #00 11 * * 1-5 /root/all_boinc_tou.sh suspend # Mid-Peak 17:00 - 19:00 #00 17 * * 1-5 /root/all_boinc_tou.sh resume # Off-Peak 19:00-07:00 00 19 * * 1-5 /root/boinc_tou.sh resume # # Winter: Nov 1st - Apr 30th # On-Peak 07:00 - 11:00 #00 07 * * 1-5 /root/all_boinc_tou.sh suspend # Mid-Peak 11:00-17:00 #00 11 * * 1-5 /root/all_boinc_tou.sh resume # On-Peak 17:00 - 19:00 #00 17 * * 1-5 /root/all_boinc_tou.sh suspend # Off-Peak 19:00-07:00 #00 19 * * 1-5 /root/all_boinc_tou.sh resume Here we have enabled BOINC applications to run during the current Season (summer) during Off-Peak hours from 7pm until 7am weekdays. Exit saving the file. If we wanted to run BOINC during the Mid-Peak as well as Off-Peak during the Summer we could do so by commenting out (prepending a “#” at the start of) the Mid-Peak line and un-commenting (removing the “#”) at the start of the On-Peak line. Windows Under Windows we can use the Task Scheduler to created two Scheduled Tasks, one to Suspend BOINC Tasks and the other to Resume them. Open the Task Scheduler (Start Menu | Windows Administrative Tools): In the Actions Pane at the Right click on “Create Task …” In the General Tab: Give the Task a Name and Description and make sure to select “Run whether the user is logged on or not” In the “Triggers” tab we create triggers to specify when we want the “Action” (suspend command) to run: Click on the “New …” button to define a new Trigger: Select “Weekly” and check “Monday” through “Friday” to have the Task run on Weekdays and set the “Start” to the time of day that BOINC should be suspended. Click “OK” to save the Trigger. Create Triggers for each time when the BOINC Projects should be suspended. Next we create an Action to suspend each BOINC Project we are running. These will require the Master URLs for each Project. These can be found by running in a Command Prompt: “C:\Program Files\BOINC\boinccmd.exe” --get_project_status | find "master URL" The leading “http(s)://” should be excluded. Click on the “Actions” tab: In the “Actions” tab click on “New” to create a new Action: Entering: Program/script: "C:\Program Files\BOINC\boinccmd.exe" including the quotes. Add arguments (optional): add: --project <master URL> suspend where “<master URL>” is one of the Master URLs found above using the “get_project_status” command. In this example we use: --project einstein.phys.uwm.edu suspend To suspend Einstein@Home. Click “OK” to save the Action. Add additional Actions for each Project you wish to follow this schedule. Click “OK” to save the Scheduled Task. You will be prompted for your Password so the Task can be run even if you are not currently logged on to the system. Following the same steps now create another Scheduled Task to resume the projects when desired changing the “argument” in the “Action” to: “--project <master URL> suspend” to “--project <master URL> resume” Holidays, when ToU rates do not apply. can be accommodated by editing the Triggers a few days in advance to not include the holiday and changing it back after the Holiday. Folding at Home For Folding at Home (F@H) things are a little more complicated. Folding at Home has a Quick Return Bonus (QRB) to encourage prompt processing of Work Units (WUs are like tasks in BOINC). If a WU is suspended the QRB, which is exponential in nature to reward participants with fast CPUs and GPUs, can dramatically decrease to the point where “dumping” the WU and starting another would net more points. “Dumping” is discouraged as it can interrupt the flow of work and progress of the Science being done. In informal testing pausing GPU WUs for more than a couple of hours is counter-productive. A better strategy for longer intervals is to evaluate the average duration of WUs for the GPUs in your system and then set the tasks to “finish” at 1/2 to 2/3 the average duration before the ToU period starts. For example, if tasks on average take 3 hours to complete on your GPU and your ToU period ends at 07:00 then you could set your WUs to finish at 05:30. In this manner, on average, half the tasks would finish between 05:30 and 07:00 and the other half between 07:00 and 08:30. This can be adjusted to meet your needs as required. The FAHClient application can be used to send commands to a locally attached F@H client or a remote client. For a locally connected client the command to pause tasks is: FAHClient --send_pause to finish tasks is: FAHClient --send_finish and to resume paused or start new tasks: FAHClient --send_unpause For remote Clients you need to first configure Remote Access and then connect to the remote client using either the FAHClient remote console port (TCP 36333) and use a scripting language such as expect or Secure Shell (SSH) to send a remote command. We will use SSH and assume that the Clients are configured to authenticate using the SSH Public Key of the user on the system initiating the command. To pause tasks on a remote system we use: ssh <hostname> ‘FAHClient --send_pause’ to finish tasks on a remote system we use: ssh <hostname> ‘FAHClient --send_finish’ and to resume paused or start new tasks on a remote system: ssh <hostname> ‘FAHClient --send_unpause’ Linux On a local host the commands can be executed on the schedule using the cron utility with the commands placed in the root crontab. Edit the root crontab: sudo crontab –e appending: # use /bin/bash to run commands, instead of the default /bin/sh SHELL=/bin/bash # Time of Day Folding # Summer: May 1st - Oct 31st # Mid-Peak 07:00 - 11:00 30 5 * * 1-5 /usr/bin/FAHClient --send-finish #00 7 * * 1-5 /usr/bin/FAHClient --send-pause # On-Peak 11:00-17:00 #30 9 * * 1-5 /usr/bin/FAHClient --send-finish #00 11 * * 1-5 /usr/bin/FAHClient --send-pause # Mid-Peak 17:00 - 19:00 #00 17 * * 1-5 /usr/bin/FAHClient --send-unpause # Off-Peak 19:00-07:00 00 19 * * 1-5 /usr/bin/FAHClient --send-unpause # # Winter: Nov 1st - Apr 30th # On-Peak 07:00 - 11:00 #30 5 * * 2-5 /usr/bin/FAHClient --send-finish #00 7 * * 1-5 /usr/bin/FAHClient --send-pause # Mid-Peak 11:00 - 17:00 #00 11 * * 2-5 /usr/bin/FAHClient --send-unpause # On-Peak 17:00 - 19:00 #30 15 * * 2-5 /usr/bin/FAHClient --send-finish #00 17 * * 2-5 /usr/bin/FAHClient --send-pause # Off-Peak 19:00 - 07:00 #00 19 * * 2-5 /usr/bin/FAHClient --send-unpause Here we have enabled F@H tasks to run during the current Season (Summer) during Off-Peak hours from 7pm until 7am weekdays setting the running tasks to “finish” starting at 05:30. Exit saving the file. If we wanted to run F@H during the Mid-Peak as well as Off-Peak during the Winter we could do so by commenting out (prepending a “#” at the start of) the Mid-Peak line and un-commenting (removing the “#”) at the start of the On-Peak line. Windows In Windows we can use the Task Scheduler as described previously to create Finish and Resume Tasks which include in the “Actions” tab: Program/script: "C:\Program Files (x86)\FAHClient\FAHClient.exe" (including the quotes) Add arguments (optional): --send-finish (OR –send-unpause as appropriate.) Multiple GPUs If you have multiple GPUs in a system and wish to specify differing times to Finish WUs then simple append the slot ID at the end the "finish" command to specify the GPU to finish at that time. Conclusion We have maximized our production in Distributed Computing applications (BOINC and/or Folding@Home) while minimizing our electricity usage during more expensive Time-of-Use rates. Here you can see the results across seven systems with multiple GPUs with summer season ToU scheduler settings: We are just running Distributed Computing applications during the least expensive ToU rates here and setting Folding@Home to “finish” Work so on average power consumption is greatly decreased when the On-Peak period starts at 07:00.

So you have remote systems Folding for you out on the Internet and want to monitor them remotely? Exposing the Web Control (TCP 7396) or Advanced Control (TCP 36330) ports can be problematic as neither protocol is encrypted and is thus susceptible to interception of your data. A better solution is to use SSH Port-Forwarding or Tunneling. The following example is for monitoring from a Windows System at home to a remote Linux system using the PuTTY SSH Client on the Windows system to create a encrypted SSH Tunnel between the Local Windows System and Remote Linux System and was inspired by this post here. On the Windows system create a PuTTY Saved Session for the Remote Host: Don't forget to click "Add" Here we are forwarding the Web Control Port on the Linux System (7396) to the same port on the Windows System so we can run Web Control or the LAR Systems Client. Run this PuTTY session. Open https://client.foldingathome.org or https://127.0.0.1:7396 See the Results from the Linux System: NOTE: You can only do this for a single system as the LAR Systems Client used the https://client.foldingathome.org URL that re-directs to localhost:7396 (127.0.0.1:7396). You could redirect other systems to other ports on the Windows system but only the one using Port 7396 will be visible to the LAR Systems Client. Re-directed systems using alternate ports can only be accessed through a browser. For example, here is another remote system we are re-redirecting to Local Port 7392 on the Windows System: But here the LAR Systems Client won't work as you can not change the Port for it but you can still access this system using the "native" address of the Windows system 127.0.0.1:7392: The same method can be used fo tunnel the Advanced Control port (TCP 36330) from a remote Linux Systems to local ports for use with the Advanced Control or HfM.net. Part 1 - FAH Control Part 2 - HfM.net Part 3 - F@H Mobile Monitor

Let's take a look at one method we can use to measure the efficiency of a Graphics Card (GPU) at various Power Limits. With electricity costs soaring globally and the need to reduce heat emissions running Folding@Home can be a delicate balancing act between contributing to a worthwhile cause and keeping your Electricity Bill low and the Temperature in your home at a reasonable level. Modern GPUs, like CPUs, have a power-efficiency curve that is exponential. At the upper end of the curve you get diminishing increases in yields. So our goal is to find the most efficient Power-Level to run a GPU at. We can define Efficiency as the Yield (PPD) at a specific Power Level (W). For convenience we will use kPPD/W as the measurement of Efficiency. What you will need: Folding at Home Advanced Control Harlam's Folding Monitor (HfM.net) (Windows only or using Wine in Linux) nvidia-smi (Bundled with NVidia drivers on Windows and Linux) Excel or Google Sheets An hour or two per GPU. The best way of measuring efficiency in Folding@Home, given the variable yields in differing Work Units (WUs), is to run a GPU at a target Power-Level over a period of several days recording the Aggregate Yield of the GPU and dividing it by the Power-Level to obtain the Efficiency at that Power-Level then adjusting the Power-Level and repeating the measurements. However, a quick indication of a GPUs efficiency can be measured by observing the changes in Yield (PPD) during a single WU as the Power-Limit is adjusted. Frame Time (TPF) is the time required to complete 1/100th of a WU. In this example we will look at a EVGA RTX 2070 Super XC Hybrid (08G-P4-3178-KR) running project 18202 as the WU. First we need to configure HfM.net to calculate it's estimate of Yield (PPD) using the last 3 Frames as the Sampling Window. A larger Sampling Window might provide more accuracy but will take more time to measure. Select Preferences in the Edit Menu in HfM and choose "Last 3 Frames" to Calculate PPD based on and Click OK. Note that TPF appears to be calculated across all Frames so PPD will be a better measurement. Select a GPU to profile taking note of which Slot on which Host it is running. First we need to determine the Minimum and Maximum Power-Levels supported by the GPU. Open a Command Prompt (Windows) or a Terminal Window (Linux) and enter nvidia-smi -q to query the capabilities of the GPUs installed in the system: Power Readings Power Management : Supported Power Draw : 126.81 W Power Limit : 125.00 W Default Power Limit : 215.00 W Enforced Power Limit : 125.00 W Min Power Limit : 125.00 W Max Power Limit : 240.00 W where: Power Limit: Current value Power-Limit is set to Power Draw: Current Power consumed by the GPU Default Power Limit: Min Power Limit: Max Power Limit: Here we see this GPU has a minimum Power of 125W, a Maximum of 240W so we will want to measure the Yields between these two Limits. We will use 25W as the step size and record Yields at: 125, 150, 175, 200, 225 and 240 Watts. Next open the Folding@Home Advanced Control application from the Task Bar. Select the system with the GPU under test click on the "Log" tab to view the log checking the "Filter" option and selecting the appropriate "Slot" from the drop-down list.: Here we can see that this WU Checkpoints every two frames. We want a consistent sampling window with the same number of Checkpoints as the Checkpoint process adds a slight delay reducing the Yield. In this case we choose to record the Yield after an odd percentage has completed every 6th percentage as we want a sampling interval (6 frames) wider than that used for the Yield estimate (3 Frames) but with a consistent number of Checkpoints (3). It is important we measure the actual Power Draw rather than the set Power-Limit as at lower and upper bounds the GPU may have trouble enforcing the Power-Limit. Wait until the WU is 5-10% complete before starting measurements. In our Command Prompt (Windows) or Terminal (Linux) enter: nvidia-smi -i 0 -l 1 --format=csv,noheader --query-gpu=temperature.gpu,power.draw,clocks.gr,fan.speed which will query GPU 0 (-i 0) on this system and display the GPU temperature, Power Draw, Graphics Clock Speed and Fan Speed once a second. While the sampling window for the current set Power-Limit is in progress we will use this to estimate the Power Draw during the sampling window. In the above example with a 125W Power-Limit we see that the GPU appears to be averaging around the set value of 125W. Next we create a spreadsheet to record our values: The first Column is our "Set" Power-limit; the second our Observed Power-Draw; The third the Percentage measurement point; the fourth the TPF in Seconds from HfM; the fifth the Yield from HfM and the 6th the calculated Efficiency (E/B/1000) in kPPD/W. In a second Administrator Command Prompt (Windows) or Terminal (Linux) set the GPU starting with the lowest Power-limit at the end of a Frame. nvidia-smi -i <GPU#> -pl <Min. Power> In this instance I used: nvidia-smi -i 0 -pl 125 Watch the nvidia-smi window during the sampling interval and record the estimate of the Power-Draw. Populate the Command Prompt or Terminal with the next set-point in preparation for when the current sampling window ends. As soon as the current sampling period finishes (watch the Log in Advanced Control) change to the next set-point (nvidia-smi -i <X> -pl <Y>) and record the TPF and PPD estimate from HfM for the previous sampling window. It helps to record the TPF and PPD values a couple of times later in the sampling interval as they should be fairly stable after 3-5 frames have completed and it will give you a good estimate of the final values. As HfM calculates the Yield (PPD) based on the last 3 Frames and our sampling window is 6 Frames you do not have to be super accurate how soon after the Frame Completion you change to the next Set Point. Here are the final values. The values seemed inconsistent after the 175W Set-Point (completed 15:02) so I took measurements adjusting the Power-Limit down from the Maximum for comparison. Perhaps the calculations performed on the WU around this point got more complicated? Here is the smoothed (5-minute average values for PPD and Power) efficiency for this GPU over the initial test run from my Zabbix server for comparison. I then calculated the Average Efficiency over the two measurements for each of the Set-Points: We can then create a scatter graph of the data including a Trend line and display the Confidence or "Fit" of the Trend line (R^2 value): For this WU on this GPU we see the Efficiency is highest at the lowest Power-Limit and gets exponentially worse as the Power-Limit is increased. To put it another way, dropping from 225W, which is close to the 217W Default, to the Minimum 125W Limit we see a 7.53% decrease in PPD for a 44.4% decrease in Power.

Hello! I've just gotten Folding to run on my Ubuntu VM with PCI passthrough in ProxMox. All was well until the WU was supposed to finish, now it's stuck at 99.99%, ETA 2 sec and I can't run commands like 'reboot', 'shutdown' or restart the FAH service.

Ive just downloaded folding@home as i got a new computer with some massive computational power and launched a fold but, i noticed that even if my computer has just firefox, discord and folding@home opened, if its set to launch on iddle, it wont. So ive set it to launch only when i work for this night to do a fold but tomorrow im gonna play some games and i dont want it to launch, What am i supposed to do to fix that ?

Here in Eastern Ontario we have Time of Use (ToU) Electricity Rates that increase the price of Electricity during "Mid Peak" and "On Peak" times during the day. If your running multiple GPUs Folding you've likely noticed the increases in your Electricity Bill and here are some hints on what you can do to keep folding during the hot months and not live in a sweat box and pay through the nose. The very first change you should contemplate is reducing the GPU's Power Limit. During normal folding in the Fall, Winter and Spring months with 10-12 GPUs I run my cards about 20% above the minimum Power Limit. I find this gives me around 90% of the PPD for 30-40% less power. NVidia Pascal and Turing GPUs, like modern CPUs, tend to run close to the edge of stability and at "stock" 100% Power Targets are not very efficient. During the summer months I run the GPUs at the minimum Power Limits for an even greater decease in Power with only a slight lessening of PPD. While using a GUI like the NVidia Control Panel or MSI Afterburner you can lower the power limits you can also use the NVidia System Management Interface: nvidia-smi -i 0 -pl 90 Here we are forcing the power-limit on GPU 0 to 90W. This will work in either Windows or Linux. You will also want to enable "Persistence Mode" so the Power Limit is not reset to the Default after the current task is finished. This command: nvidia-smi -pm 1 will enable persistence mode for all GPUs. A specific GPU can be specified also using the "-i <X>" switch where "<X> is the Device ID shown in nvidia-smi output. Scheduling Folding only during less expensive ToU periods can be accomplished but will take a bit of work to setup. Here we leverage the ability of the FAHClient program to send commands to a running "Slot" (GPU). What we need to do is tell the GPU slots to "Finish" about half the average time it takes for that GPU to complete a Work Unit (WU) before the start of the ToU rate period. In my case my GPUs typically complete a WU in about 3 hours when running at minimum power limits so I schedule the "Finish" command to run at 05:30 as the ToU period here starts at 07:00. This results in the GPUs finishing their current WUs then "Pausing." When the ToU period ends you schedule a "Un-Pause" command to be sent to resume folding. In my case the ToU rates end at 19:00. In Linux you could use the "cron" scheduler thus: # use /bin/bash to run commands, instead of the default /bin/sh SHELL=/bin/bash # Time of Day Folding - Summer #Mid-Peak 07:00 - 11:00 30 5 * * 1-5 /usr/bin/FAHClient --send-finish #On-Peak 11:00-17:00 #30 9 * * 1-5 /usr/bin/FAHClient --send-finish #Mid-Peak 17:00 - 19:00 #00 17 * * 1-5 /usr/bin/FAHClient --send-unpause #Off-Peak 19:00-07:00 00 19 * * 1-5 /usr/bin/FAHClient --send-unpause Windows users can utilize the Command Scheduler and the same commands: 'C:\Program Files (x86)\FAHClient\FAHClient.exe --send-finish' 'C:\Program Files (x86)\FAHClient\FAHClient.exe --send-unpause' The result looks something like this: Here 5 of my systems are scheduled to "Finish" at 05:30 and by 07:00 my GPU power consumption has dropped from 1kW to 300W with the last couple of Slots "Pausing" by ~07:20. Note: I am also running some BOINC tasks on the Blue and Dark Red systems accounting for the periodic power spikes. And here's what it looks like over the last couple of weeks: So you can see I run 24hours during weekends and holidays and about 12 hours (19:00-07:00) during weekdays when ToU rates are in effect.

I have been folding at home on my rather old iBuyPower gaming PC that I also still use for work. However, it's not going very fast, and I would like to increase my folding power, plus I am also due for upgrading my work computer. I'm not very knowledgeable about computer hardware, so I was wondering if I could get some pointers here. 1) What would be a good desktop PC I can buy new that I could use for my regular work (some minor video editing and Photoshop involved, but nothing major), but would also be good for folding in the background? Looking at prices up to around $1300. 2) How can I optimize my old PC for folding? I'd like to just run it 24/7 for only folding. The current specs are as follows: Processor: Intel(R) Core(TM) i7-2600K CPU @ 3.40GHz Memory (RAM): 16.0 GB Graphics: NVIDIA GeForce GTX 560 Gaming graphics: 9975 MB Total available graphics memory System type 64-bit operating system Number of processor cores: 4 Is there a graphics card that is under around $400 that I could replace the old one with that would significantly increase the folding capacities? Thanks!

Weird question... Can anyone recommend games that the play while folding in the background? I try to run it as much as possible, but I did build a gaming PC for a reason. I have Music Racer which doesn't slow down F@H much but I wonder if anyone else knows games can be played on top of folding without losing too many points/burning down their house. (I do only have 1 GPU, will need a PSU upgrade before even thinking about just chucking another one in for 24/7 folding)

Motherboard: ASRock Rack TRX40D8-2N2T Cpu: AMD Threadripper 3970X Ram : 128gb G-Skill 3600 GPUs: 4 PNY 3090s & 4 Zotac 3090s on EKWB waterblocks Case: Custom design from Protocase PCIe backplanes: OneStop Systems PSUs: 2x 2000w FSP Canon & 2 500w FSP FlexATX Internal pump: Swiftech MCP35X Cooling System: Koolance ALR-4500C Performance: Desmond MD: 590 ns/day per card FAH: 44,000,000 PPD

I have setup a dedicated folding@home VM running on ubuntu (3 Cores, 3gb of RAM) on my FreeNAS (FreeNAS-11.3-U4.1), and it is shutting itself down when it is not open in a VNC for an extended period of time. Is there a way that I can stop this from happening. Thanks in advance

Now that were about to start the Folding Month and many are going to start folding 24x7 for a protracted period you may want to lower your GPUs power limit. Experience has shown that there is an exponential increase in power required to achieve the highest range of boost clocks. Typically you see 20-30% additional power required at the high end of the boost table to achieve 5-10% additional clock. Reducing your Power Levels for long-term use will keep you GPUs cooler and your systems quieter. I typically use a power-limit set to 75-80% of the Founder's Edition (FE) Power Limit for daily operation. It is important to note that most Add-in-Board (AIB) partner's cards have default power-limits that typically exceed the FE values so if your using AfterBurner, Precision X-1 or a similar control with a % Slider to know that your 100% value needs to be scaled to the FE value for running the cards more efficiently. Here are the Pascal and Turing FE power limits for reference: Model FE_Def 80%_FE 75%FE 1060 120W 96W 90W 1070 150W 120W 90W 1070Ti 180W 144W 135W 1080 180W 144W 135W 1080Ti 250W 200W 188W 1660 120W 96W 90W 1660Su 125W 100W 94W 1660Ti 120W 96W 90W 2060 160W 128W 120W 2060Su 175W 140W 131W 2070-A 175W 140W 131W 2070Su 215W 172W 161W 2080 215W 172W 161W 2080Su 250W 200W 188W 2080Ti 250W 200W 188W Under Windows or Linux you can use the nvidia-smi tool to set the power limit from the command line or a script. First you have to enable "persistence mode" to have the setting "stick" between jobs: nvidia-smi -pm 1 Then set the power-limit: nvidia-smi -i 0 -pl 160 to set a 160W power limit for GPU0.

500th POST YAY I was getting my system out of the dust for folding@home and I have a problem. It has a Quadro 600 in it but it cant fold. The CPU folding works fine but the GPU is just stuck on waiting for idle but I have set it to fold permanently not just when idle.

I keep getting 16:41:21:WARNING:WU00:FS00:Exception: Failed to send results to work server: Failed to connect to 40.114.52.201:80: No connection could be made because the target machine actively refused it. Can I change the IP to make it send the results to a working server? I can see on https://apps.foldingathome.org/serverstats that 40.114.52.201 is down.

Summer Folding Sprint of 2020 Starts June 13th(00:00 BST) Ends June, 19th (23:59 BST) Sign up for the event here: Sign ups closed at 23:30BST, 11th June. REGISTRATION HAS NOW CLOSED FOR THIS EVENT! If you are unsure on how to fill in the form ask on the thread below. If you make a mistake filling out the form please use the thread linked below. https://linustechtips.com/main/topic/1204086-folding-sprint-2020-correction-thread/ Folding@home team LTT id#: 223518 (This event is only for folding for team LTT you will not qualify if you are folding independent or for another team, sorry.) This event will NOT be eligible for F@H event badges. Please read the whole of this post before asking any questions and use the links provided at the end for help and support! If anyone is willing to help with data handling please PM me ASAP! Please follow this thread to keep up to date! Minimum Participation Requirements For Prizes 5 Days with activity* & 300,000 Points (*activity is defined as completing at least 1WU for the 24 hour period) Prizes!!! (More to come soon) Community donated prizes: 20x Random Steam keys - Community Pool 2x 20USD Steam Gift Card - Donated by @Zberg 2x 20USD Steam Gift Card - Donated by @Jawa_Juice Draw: All Ranks Summer is that time when it gets hot outside, just thought you may need a reminder with how long some of us have been in lockdown. Many of us on the folding front like to gear down a little during this strange mystical time of higher temperatures as we believe all our folding activities have heated up the world too much so we want to let it cool of a little. Seriously though, it can be hard to stay motivated during summer as the heat starts to climb, so to reward you for your efforts I like to run a small event. We have all the motivation we need currently with the ongoing crisis we face so I won't waffle on too much. I just want you all to know that your efforts are appreciated. What is Folding@Home Folding@home is a network of volunteer computers distributed around the world that aims to perform biomedical research with the single intent of helping to further understand and develop cures for a range of diseases such as; Alzheimer's, cancer, and Parkinson's and most recently COVID19. The exact research that is done is simulating the 'folding' of proteins in the body, this is important because the function of a protein id directly related to its physical shape. And this, when the protein is created in the body it needs to reshuffle its shape to get into the correct structure to perform its task. Many illnesses can be linked to faulty proteins in the body such as many cancers and neurological issues, along with a wide number of other general health concerns. Folding@home is one of the world's fastest computing systems, over the last few months reaching a speed of around 2.5 Exaflops due to massive support taking the fight to COVID19. Currently the network sits just over the 2 Exaflop mark, Making it four times faster than the top 10 supercomputers combined. PASSKEYS! (they're really important) Don't forget to get yourself a passkey from the link below to ensure that you hit the points requirement, the passkey is a feature that was added a while ago to the Folding Client that helps to authenticate each user on the network, an added bonus of this is the fact that it allows you to qualify for QRB(Quick Return Bonus) Points, QRBs are extra points you earn for submitting work units more quickly, such as if you have faster hardware or let the client fold full time, rather than on idle. QRB credit is awarded after 10 WUs have been submitted. You can get your passkey from the link below. https://apps.foldingathome.org/getpasskey Please remember that I will be writing my usual daily update blog once the event kicks off, the blog can be found linked below. https://linustechtips.com/main/blogs/entry/1853-prelude/ This is just a PSA for the new guys here, the folding team is historically a small close knit community, so here's a few things I'd like you all to keep in mind. It doesn't hurt to say thank you, if someone has genuinely helped you out don't forget to drop a reaction on their posts, help others where ever you can and finally we are a team first and always. Check your stats out here! Bare in mind it can take some time for your first WUs to appear so leave it a day or two. https://folding.extremeoverclocking.com/search.php

In an effort to expand my Compute capabilities I recently picked up a i9-9900k and a 3900x. The 3900x has proven relatively plug-and-play installing nicely in my Aorus x570 Pro WiFi and the performance showing a nice uplift after replacing the "adequate" stock cooler with a NH-D15. The 9900k, however, has lived up to its reputation as a thermal monster. Making matters worse the GigaByte z370 Gaming 5 it has been installed in suffers from a rather weak VRM (4-phase) that is itself prone to overheating. A first attempt at cooling this beast using a Hyper 212 Black with a Noctua NF-A12iPPC2000 PWM strapped onto it showed poor results. While perhaps adequate for light gaming my requirements are for it to remain stable under 24x7 compute and even with an under-volt and a -300MHz AVX off-set and 4.6GHz all-core limit could not pass Prime95 torture test (mprime -t) of longer duration. Replacing the Hyper 212 with a 120mm CLC with the NF-A12iPPC2000 showed similar results. Next up was an upgrade to an EVGA 280mm CLC and a Fractal Meshify S2 to house the system in. A first attempt at a high all-core overclock with an under-volt showed that 4.6GHz all-core at 1.160V Vcore appeared to be the best attainable while passing Prime95 with AVX enabled. Futher testing showed, however, that LLC at Turbo and Vcore at 1.250V were required for stability. Again there were some stability issues and after dropping the all-core down to 4.5GHz and Vcore to 1.130V the system remained stable for Folding with the Cores at 64-72C, VRM at 81C (17C Ambient). Stability was still elusive though with the system randomly locking up after 8 or 9 hours with nothing in the logs (hard lock) likely indicating a hardware issue. After clearing the CMOS settings and running Prime95 it was observed that the VRM was hitting 115C with no end in sight during small FFT tests with AVX enabled. Removing the plastic I/O shroud on the motherboard the plastic spacers on the VRM heat-sinks were removed to allow better contact of the heat-sinks to the MOSFETs and a 80mm fan installed to provide airflow over the VRMs. This improved things but only slightly. Prime95 Torture tests were then run while observing the VRM thermals. An AVX off-set of -300MHz was found to be required at stock settings to keep the VRM thermals during small FFTs under 100C. A Prime95 Torture Test was run overnight (17 hours) and no errors or warnings were recorded. The system has returned to folding driving 2 RTX 2070 Super Hybrids and with 14 threads CPU Folding (an 8 and a 6-thread slot) with no stability issues in almost 48-hours. The UPS shows the system having an idle load of 55W and 225W when just the CPU slots are enabled so the CPU draws about an additional 170W folding. Hindsight being 20/20 the better approach would have been to just retire the z370 motherboard and get a new x570 board and another 3900x. Realistically this system would need a z390 motherboard with a beefier VRM to work well and the x570 with a 3900x would still crush a 9900k performance wise. At some point, when I can take the system off-line for an extended period, I intend to see how much I can lower Vcore as that could both alleviate the strain on the VRM and may potentially allow a slight increase in the maximum all-core clock.

Hi guys this is my post from another thread they recommend i post here.

Creating a place to discuss the Folding@Home Babysitter script It has been noticed that pause and un-pausing slots that are stuck in a waiting status looking for work has improved the clients ability to connect and download work units. That's where the Babysitter script that @danielocdh wrote comes in, it checks the Folding@Home client periodically and pauses and un-pauses slots that are stuck waiting on Work Server Assignment. A few people are using this now to try to help manage Folding@Home clients, so I figured it might be easier to create a topic on it for instructions, feedback, in case people are having issues and to provide updates. Easier than running around the different topics that have referenced it. I've been working with @danielocdh to update this script here and there to ensure it works with the recently released version of the Folding@Home Client and fix other issues and add new features It can be found on GitHub currently, as of writing this topic, the script is at version 1.8 and will now tell you periodically if there are updates. At the top of the script you can find options as well as a how to for installing Python 3 Installing Python 3 on Windows: Installing Babysitter Script on Windows: Options Available:

I thought everyone would appreciate this little nugget. Over a three week period, the team DOUBLED our total point value!

Hello, Got a system build for mining that I would be paused for High-end gaming. AMD 1700 (AIO water cooled.) pushed to 3.9 2 580 Sapphire rx Nitro+ special. (The blue version.) The GPUS were bought 2nd hand from a Mining farm. 1 tops at 1440, the other doesn't make it past 1400 with out issues. Game is obviously no problem. I ran them in a test bed open air style for about a year getting about half what I paid for them (Random alt coins. trading and switching got stupid.) These cards are used to crunching numbers. Now I am verging on 1 million points a day. (I did upgrade my CPU to a 3rd gen Ryzen 5.) Just looking for that push past. Currently at 922799. Any settings for the 580's I could try? I played with BIOS quite a few times and wont accept any of those suggestions. (please don't suggest anything like that.) 18.*7* works best for compute 19-+ is all gaming based and crashes intently. Mostly memory and power limits is what I am hoping to try. Feel free to toss some R5 3600 settings out I get around 4.2 but the WU's don't seem to change in speed. So Ill try to push but GPU's are WELL burnt into a high heat processing and are work horses that could use some tweaks.

Hey guys, I have recently started folding. Origoanly both my GPU (GTX 1080ti) and CPU (i7-8086k) were working. After a few days my GPU is now stuck on waitng for WS Assignment, I have tried most of the stuff in other posts, but it hasn't worked. ANy help? Here is my log after some troubleshooting. It apperas to be a host issue. If it is, how do I change my host to allow for me to fold? 08:19:17:Adding folding slot 01: READY cpu:12 08:19:17:Adding folding slot 03: READY gpu:0:GP102 [GeForce GTX 1080 Ti] 11380 08:19:17:Removing old file 'configs/config-20200410-033658.xml' 08:19:17:Saving configuration to config.xml 08:19:17:<config> 08:19:17: <!-- Network --> 08:19:17: <proxy v=':8080'/> 08:19:17: 08:19:17: <!-- Slot Control --> 08:19:17: <power v='full'/> 08:19:17: 08:19:17: <!-- User Information --> 08:19:17: <passkey v='********************************'/> 08:19:17: <team v='260741'/> 08:19:17: <user v='Jagger_Winkler'/> 08:19:17: 08:19:17: <!-- Folding Slots --> 08:19:17: <slot id='1' type='CPU'/> 08:19:17: <slot id='3' type='GPU'/> 08:19:17:</config> 08:19:17:FS00:Shutting core down 08:19:17:WU00:FS02:Slot ID 2 no longer exists and not yet downloaded, dumping 08:19:17:WU00:FS02:Cleaning up 08:19:17:WU01:FS00:0xa7:WARNING:Console control signal 1 on PID 12732 08:19:17:WU01:FS00:0xa7:Exiting, please wait. . . 08:19:17:WU00:FS01:Connecting to 65.254.110.245:8080 08:19:18:WARNING:WU00:FS01:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:19:18:WU00:FS01:Connecting to 18.218.241.186:80 08:19:18:WU02:FS03:Connecting to 65.254.110.245:8080 08:19:18:WARNING:WU02:FS03:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:19:18:WU02:FS03:Connecting to 18.218.241.186:80 08:19:20:WU01:FS00:0xa7:Folding@home Core Shutdown: INTERRUPTED 08:19:20:WU01:FS00:FahCore returned: INTERRUPTED (102 = 0x66) 08:19:21:WARNING:WU01:Slot ID 0 no longer exists, migrating to FS01 08:19:21:WU01:Starting 08:19:21:WU01:Running FahCore: "C:\Program Files (x86)\FAHClient/FAHCoreWrapper.exe" C:\Users\hjagg\AppData\Roaming\FAHClient\cores/cores.foldingathome.org/v7/win/64bit/avx/Core_a7.fah/FahCore_a7.exe -dir 01 -suffix 01 -version 705 -lifeline 14012 -checkpoint 15 -np 11 08:19:21:WU01:Started FahCore on PID 23780 08:19:22:WU01:Core PID:19268 08:19:22:WU01:FahCore 0xa7 started 08:19:22:WU01:FS01:0xa7:*********************** Log Started 2020-04-12T08:19:22Z *********************** 08:19:22:WU01:FS01:0xa7:************************** Gromacs Folding@home Core *************************** 08:19:22:WU01:FS01:0xa7: Type: 0xa7 08:19:22:WU01:FS01:0xa7: Core: Gromacs 08:19:22:WU01:FS01:0xa7: Args: -dir 01 -suffix 01 -version 705 -lifeline 23780 -checkpoint 15 -np 08:19:22:WU01:FS01:0xa7: 11 08:19:22:WU01:FS01:0xa7:************************************ CBang ************************************* 08:19:22:WU01:FS01:0xa7: Date: Oct 26 2019 08:19:22:WU01:FS01:0xa7: Time: 01:38:25 08:19:22:WU01:FS01:0xa7: Revision: c46a1a011a24143739ac7218c5a435f66777f62f 08:19:22:WU01:FS01:0xa7: Branch: master 08:19:22:WU01:FS01:0xa7: Compiler: Visual C++ 2008 08:19:22:WU01:FS01:0xa7: Options: /TP /nologo /EHa /wd4297 /wd4103 /Ox /MT 08:19:22:WU01:FS01:0xa7: Platform: win32 10 08:19:22:WU01:FS01:0xa7: Bits: 64 08:19:22:WU01:FS01:0xa7: Mode: Release 08:19:22:WU01:FS01:0xa7:************************************ System ************************************ 08:19:22:WU01:FS01:0xa7: CPU: Intel(R) Core(TM) i7-8086K CPU @ 4.00GHz 08:19:22:WU01:FS01:0xa7: CPU ID: GenuineIntel Family 6 Model 158 Stepping 10 08:19:22:WU01:FS01:0xa7: CPUs: 12 08:19:22:WU01:FS01:0xa7: Memory: 31.93GiB 08:19:22:WU01:FS01:0xa7:Free Memory: 25.86GiB 08:19:22:WU01:FS01:0xa7: Threads: WINDOWS_THREADS 08:19:22:WU01:FS01:0xa7: OS Version: 6.2 08:19:22:WU01:FS01:0xa7:Has Battery: false 08:19:22:WU01:FS01:0xa7: On Battery: false 08:19:22:WU01:FS01:0xa7: UTC Offset: -6 08:19:22:WU01:FS01:0xa7: PID: 19268 08:19:22:WU01:FS01:0xa7: CWD: C:\Users\(Removed)\AppData\Roaming\FAHClient\work 08:19:22:WU01:FS01:0xa7:******************************** Build - libFAH ******************************** 08:19:22:WU01:FS01:0xa7: Version: 0.0.18 08:19:22:WU01:FS01:0xa7: Author: Joseph Coffland <joseph@cauldrondevelopment.com> 08:19:22:WU01:FS01:0xa7: Copyright: 2019 foldingathome.org 08:19:22:WU01:FS01:0xa7: Homepage: https://foldingathome.org/ 08:19:22:WU01:FS01:0xa7: Date: Oct 26 2019 08:19:22:WU01:FS01:0xa7: Time: 01:52:30 08:19:22:WU01:FS01:0xa7: Revision: c1e3513b1bc0c16013668f2173ee969e5995b38e 08:19:22:WU01:FS01:0xa7: Branch: master 08:19:22:WU01:FS01:0xa7: Compiler: Visual C++ 2008 08:19:22:WU01:FS01:0xa7: Options: /TP /nologo /EHa /wd4297 /wd4103 /Ox /MT 08:19:22:WU01:FS01:0xa7: Platform: win32 10 08:19:22:WU01:FS01:0xa7: Bits: 64 08:19:22:WU01:FS01:0xa7: Mode: Release 08:19:22:WU01:FS01:0xa7:************************************ Build ************************************* 08:19:22:WU01:FS01:0xa7: SIMD: avx_256 08:19:22:WU01:FS01:0xa7:******************************************************************************** 08:19:22:WU01:FS01:0xa7:Project: 14402 (Run 0, Clone 1163, Gen 86) 08:19:22:WU01:FS01:0xa7:Unit: 0x0000006380fccb095dcb2cb44cc470ba 08:19:22:WU01:FS01:0xa7:Digital signatures verified 08:19:22:WU01:FS01:0xa7:Reducing thread count from 11 to 10 to avoid domain decomposition by a prime number > 3 08:19:22:WU01:FS01:0xa7:Calling: mdrun -s frame86.tpr -o frame86.trr -x frame86.xtc -cpi state.cpt -cpt 15 -nt 10 08:19:22:WU01:FS01:0xa7:Steps: first=10750000 total=125000 08:19:24:WU01:FS01:0xa7:Completed 33132 out of 125000 steps (26%) 08:19:39:WARNING:WU00:FS01:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:19:39:ERROR:WU00:FS01:Exception: Could not get an assignment 08:19:39:WU00:FS01:Connecting to 65.254.110.245:8080 08:19:39:WARNING:WU02:FS03:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:19:39:ERROR:WU02:FS03:Exception: Could not get an assignment 08:19:39:WU02:FS03:Connecting to 65.254.110.245:8080 08:19:39:WARNING:WU00:FS01:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:19:39:WU00:FS01:Connecting to 18.218.241.186:80 08:19:40:WARNING:WU02:FS03:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:19:40:WU02:FS03:Connecting to 18.218.241.186:80 08:19:44:Removing old file 'configs/config-20200410-062706.xml' 08:19:44:Saving configuration to config.xml 08:19:44:<config> 08:19:44: <!-- Network --> 08:19:44: <proxy v=':8080'/> 08:19:44: 08:19:44: <!-- Slot Control --> 08:19:44: <power v='full'/> 08:19:44: 08:19:44: <!-- User Information --> 08:19:44: <passkey v='********************************'/> 08:19:44: <team v='260741'/> 08:19:44: <user v='(removed)'/> 08:19:44: 08:19:44: <!-- Folding Slots --> 08:19:44: <slot id='1' type='CPU'/> 08:19:44: <slot id='3' type='GPU'/> 08:19:44:</config> 08:19:55:WU01:FS01:0xa7:Completed 33750 out of 125000 steps (27%) 08:20:01:WARNING:WU00:FS01:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:20:01:ERROR:WU00:FS01:Exception: Could not get an assignment 08:20:01:WARNING:WU02:FS03:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:20:01:ERROR:WU02:FS03:Exception: Could not get an assignment 08:20:39:WU00:FS01:Connecting to 65.254.110.245:8080 08:20:39:WARNING:WU00:FS01:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:20:39:WU00:FS01:Connecting to 18.218.241.186:80 08:20:40:WU02:FS03:Connecting to 65.254.110.245:8080 08:20:40:WARNING:WU02:FS03:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:20:40:WU02:FS03:Connecting to 18.218.241.186:80 08:20:55:WU01:FS01:0xa7:Completed 35000 out of 125000 steps (28%) 08:21:00:WARNING:WU00:FS01:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:21:00:ERROR:WU00:FS01:Exception: Could not get an assignment 08:21:01:WARNING:WU02:FS03:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:21:01:ERROR:WU02:FS03:Exception: Could not get an assignment 08:21:56:WU01:FS01:0xa7:Completed 36250 out of 125000 steps (29%) 08:22:16:WU00:FS01:Connecting to 65.254.110.245:8080 08:22:17:WU00:FS01:Assigned to work server 13.82.98.119 08:22:17:WU00:FS01:Requesting new work unit for slot 01: RUNNING cpu:11 from 13.82.98.119 08:22:17:WU00:FS01:Connecting to 13.82.98.119:8080 08:22:17:WU02:FS03:Connecting to 65.254.110.245:8080 08:22:17:WARNING:WU02:FS03:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:22:17:WU02:FS03:Connecting to 18.218.241.186:80 08:22:17:WU00:FS01:Downloading 7.46MiB 08:22:20:WU00:FS01:Download complete 08:22:20:WU00:FS01:Received Unit: id:00 state:DOWNLOAD error:NO_ERROR project:13871 run:0 clone:3752 gen:45 core:0xa7 unit:0x000000370d5262775e7bbb92ff018fdb 08:22:38:WARNING:WU02:FS03:Failed to get assignment from '18.218.241.186:80': Failed to connect to 18.218.241.186:80: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond. 08:22:38:ERROR:WU02:FS03:Exception: Could not get an assignment 08:22:55:WU01:FS01:0xa7:Completed 37500 out of 125000 steps (30%) 08:23:55:WU01:FS01:0xa7:Completed 38750 out of 125000 steps (31%) 08:24:54:WU02:FS03:Connecting to 65.254.110.245:8080 08:24:54:WARNING:WU02:FS03:Failed to get assignment from '65.254.110.245:8080': No WUs available for this configuration 08:24:54:WU02:FS03:Connecting to 18.218.241.186:80 08:24:54:WU01:FS01:0xa7:Completed 40000 out of 125000 steps (32%)

Introduction This is an extension of the already existing guide written by @Metallus97 for using cloud GPUs to run folding applications. I will be referring to some steps in that guide, so it will probably be good to have it open in an other tab. That guide shows you how to set up Folding at Home for a normal google cloud instance for 1.7MPPD+ for free for almost two weeks. In this guide I will be showing you how to set up Folding at Home to run on "preemptible" google cloud instances for a little under half the cost with little/no PPD penalty, that gives us almost a month of GPU time at around 1.7MPPD for free! These instances also last at the very most 24 hours before they get shutdown, depending on time of day I have had instances up for a range between 1 and 10 hours so it required some extra setup to do constant, almost uninterrupted folding using this instance type (Don't worry about that though, I have made a Terraform project to to almost ALL of the setup for you!). Lets get started! 1. Pick where you want to run your folding vms. Using this calculator, change the machine class to "Preemptible" and "Machine type" to "n1-standard-2" or whichever has at least one core per GPU that you want to have. Add the GPUs that you want and click add to estimate. Different regions have different costs so you can click "edit" to test which regions you will get the best bang for your buck, and/or which are the best places to run these vms because they are near you. I have chosen what I found to be the cheapest region to use, so if you just want to just get started you can ignore this step, and steps 8 and 9. 2. Next off, you will need to follow steps 1.1-1.5 on @Metallus97's guide. 3. Then, download and install Terraform as that is what we will be using to automatically set up almost everything you will need! 4. Download and unzip this file. 5. Open `terraform.tfvars` in a text editor. 6. in the `terraform.tfvars` file you should: - Fill in remote_access_ip and remote_access_password if you want to access BOINC or F@H Remotely(If you leave the password blank, Terraform will generate a password for you). - Fill in your F@H username, passkey, and team if you want to use Folding at Home - Choose how many of each instance type you want to be running (F@H exclusive, BOINC exclusive, and both F@H and BOINC) 7. If you want, in `terraform.tfvars` you can also set the machine type, GPU type and count to what you chose before, or leave the defaults for a 1 GPU Tesla P100 instance for a single instance of the best $/PPD/Day configuration for F@H. (More GPUs as long as you keep 1 core per GPU will yeild more PPD and the same bang for buck, but give you less time. The default config gives you almost a month!). You can ignore these steps if you didn't want to do the work of choosing regions yourself, the project is configured to use what I found to be the cheapest regions by default. 10. Open your project dashboard and add `project=` in `terraform.tfvars` to the "Project ID" in your dashboard. e.g `project="my_project_id"`. 11. Go to the functions and scheduler web pages and wait for them to initialise, when asked to set a region for the scheduler pick what you chose for the app engine (or if you are going with the defaults, select "us-west2". 12. Go to the service accounts page and add a service account for terraform and add these rolls: Cloud Functions Developer Cloud Scheduler Admin Compute Admin Service Account User Pub/Sub Editor Storage Admin Then create and download the account key. 13. Rename the downloaded .json file to "credentials.json" and move it into the `resources/` folder in the unzipped project folder. 14. Open the project folder in a terminal, and run: `terraform init` $ terraform init Initializing the backend... Initializing provider plugins... - Checking for available provider plugins... - Downloading plugin for provider "archive" (hashicorp/archive) 1.3.0... - Downloading plugin for provider "random" (hashicorp/random) 2.2.1... - Downloading plugin for provider "google" (hashicorp/google) 3.16.0... Terraform has been successfully initialized! You may now begin working with Terraform. Try running "terraform plan" to see any changes that are required for your infrastructure. All Terraform commands should now work. If you ever set or change modules or backend configuration for Terraform, rerun this command to reinitialize your working directory. If you forget, other commands will detect it and remind you to do so if necessary. Then `terraform apply` $ terraform apply data.archive_file.start_vm_function_source: Refreshing state... An execution plan has been generated and is shown below. Resource actions are indicated with the following symbols: + create Terraform will perform the following actions: ...... Plan: 10 to add, 0 to change, 0 to destroy. Do you want to perform these actions? Terraform will perform the actions described above. Only 'yes' will be accepted to approve. Enter a value: and enter "yes". 15. Add your instance as a remote client (if you configured an access IP and password) (using port 36331 for F@H) and wait for it to come up. You might need to wait a while for the instance to finish installing the Nvidia drivers and F@H client and/or BOINC client. You can keep tabs on the installation progress by running: tail -n 100 -f /var/log/cloud-init-output.log on the instance over SSH (see how below). Notes You can SSH (remote terminal) into the instance by clicking this on this page: When you are finished (probably when you have run out of free credit), open the project folder in a terminal again and run: terraform destroy EDIT: I have been dealing with strange FAHCore interruptions (code 102) on my GCE instances (on GPU units). After looking through the system logs and resource usage it turns out that F@H was chewing up all available memory and then getting OOM killed. If you are dealing with this, try changing the machine type to `n1-standard-2`. After waiting to see stability I may change the default machine type to this even though it costs a bit more (but negligible compared to the GPU costs anyway). EDIT2: I should also note, this setup doesn't do anything special to for BOINC to handle the instances starting and stopped. I couldn't find much online and what I did find suggests that BOINC already handles this fine. Let me know if you have any problems or know otherwise.

Yesterday, my sister took on a large math problem involving the LTT folding team stats. The attached graph is what was created to determine when our team, LinusTechTips_Team, will overtake the other folding teams above it. At this pace we will catch CureCoin on Nov 19th, 2020. All credit for the math work goes to my sister on this one! The colored graph below shows each time and the intersecting points mark the days until the team is passed. "The lines represent the total points each of the top four teams will have, as time passes, given their present rates of change." As of yesterday, "in 38 days, LTT will pass EVGA and in 88 days, pass Default. It will take until November for LTT to pass CureCoin and be first, so keep folding!" - Quotes from my sister. LinusTechTips_Team is going strong. I myself am folding for the team and donating my computer power when I am not editing video. Let's get LTT up the charts!

Currently using folding at home for both gpu and cpu but I have noticed my gpu is appearing in the advanced controller as a R9 200 series.... Even though my gpu is a R9 380. Does anyone else have this and know a fix for it? As I believe it is actually making the work units take longer than they should.