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  1. This has been copied from the original Community board, it will be updated shortly This will be a place for events within the Folding (and sometimes Boinc) community to be posted. It is also a good place to introduce yourself to the rest of the team and ask questions if you have them. If you have an event you would like to organize post it here and PM me about it. Current or upcoming events: In case you are actually living under a rock there is currently a global pandemic of COVID-19 which team LTT and folding@home is working to solve!!! (If you have an event you are trying to organize or would like to participate in please post in this thread and PM me) Nothing right now to announce. But a lot of changes have happened as we have a new Folding team leader: Congratulations to @GOTSpectrum Also check the badge thread as there is now also a diamond level badge for anyone with more than 1,000,000,000 points. If you need to check on final places or prize winners for Folding Month 2019 please check the blog post below as it will have all the information for you. Folding@home team LTT id#: 223518 Boinc teams are all called LinusTechTips_Team Results from past events: Folding month 2019!!! Sprint for 10th! BOINC Pentathlon 2019 LTT Official Folding Month 2018! First LTT folding week results (3/26-4/1/2018): https://docs.google.com/spreadsheets/d/1NerB4jOfgEG_l9mcxxMNTe6hboswk6V-hLiSLMDp7gc/edit?usp=sharing My folding story and also my reasoning for the first event: It was a long time ago when discovered this thing called distributed computing and a piece of software that will use your computer power to help fight against many diseases including cancer . When I started folding I also joined the Linus Tech Tips team (it was actually @Slick's old Ultimate Distributed Computing build that got me into it.) and considering that the mining craze had died down a bit and its still cold for those of us in the northern hemisphere. I was wondering if we could get the whole community together to donate as much of their compute power as they can to Folding At Home (yes it is true that every little bit helps) for some amount of time (title says a week but can easily be extended if we can do it). Obviously the encouragement is to fold to the Linus Tech Tips Team #223518 but since folding is a good cause no matter what there would be no complaints about folding for another team. But one of the pieces of this that really encouraged me was looking at the team ranking for LTT and realizing that we have dropped to 14th considering that when we started we were at least 11th. Long story short fold (preferably for LTT), get your friends folding get their friends folding and even if you bring in complete noobs we have a whole community here to help them. I will link the guides here as well as the video that got me into it. For those that still need some encouragement here's the video that started it all for me: New F@H (Folding@Home) FAQ & Guide for all info on how to install and use F@H: If you are too lazy for all of that here is a link to the site to download it https://foldingathome.org/#downloads If any of you have any questions or need help getting your system set up (there are some things that can be tricky at first and I know sometimes reading the guides can be tedious) please feel free to post here where people with more experience than I can help you or pm me if need be. TLDR: A team that folds together... stays together?... you know what I'm sticking with that one. Huge thank you to everyone involved from all of you and the moderators getting this pinned to people just helping each other out on setups and spreading the word to anyone here who is just folding. I never though that this was going to pick up any traction at all and now its an actual bonafide event. So thank you all and let the folding begin!
  2. 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.
  3. 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!
  4. There's been a few posts lately where people have been having issues accessing a Folding Rig from another Computer using the Advanced Control client. Couple of important points. Even on your local machine Folding is divided between two parts. The Server which manages folding the Work Units (WUs) downloaded from the Work Servers and the Client that allows you to Configure, Monitor and Control the Server. Just to be confusing the server is called FAHClient and the Client can be either the Advanced Control Python Application or the Web Server built in to FAHClient. These two control processes on FAHClient have their access restricted by default to just the computer they are running on (the "localhost" or 127.0.0.1 (loopback IP Address)). The WebControl runs on TCP Port 7396 and can be accessed by any browser on the computer the Server is running on by the URL: http://127.0.0.1:7396 where 127.0.0.1 is the IP Address referring to the localhost or the IP address of the computer can be used: http://<ip address>:7396 The Advanced Control uses TCP port 36330 ( and can be also accessed using using any TELNET client that supports UNIX terminal emulation such as PuTTY, which the Windows Telnet Client, unfortunately does not ) In order to permit access to either the Web Control or using the Advanced client on another PC you have to allow access on the remote system. Assuming you are on a Local Area Network (LAN) and protected by a router with a firewall blocking external connections the easiest way of doing this is to use the Advanced Control application on the system you want to manage remotely to add the IP Network Address and Mask that will allow all the hosts on your LAN Access without a password. Using a command prompt and running the command: ipconfig you can display your IPv4 address and then click on the "Configuration" button in Advanced Control enter at the bottom of the "Remote Access" tab your network address and mask in BOTH the "IP Address Restriction" and "Passwordless IP Address Restriction" Dialogs. You LAN's IP Network will typically be 192.168.1.0/24 as this is the default for most home routers. Note that you MUST leave in the localhost address 127.0.01 and use spaces to separate the values. Once you have entered the new values and saved them you have to close the Advanced Control Application and Stop and Restart the FAHClient server. If you are in the middle of folding a WU first pause the Work Unit before closing the Advanced Control. To stop the server right-click on the "Folding" applet in the Taskbar and select quit. To restart the server click on the "Folding@home" desktop shortcut which will also launch the Web Control. Un Pause the Work Unit to Resume Folding and then try to access the Sever from another computer using either a web browser or the Advanced Control if it installed. Part 2 - HFM.net Part 3 - F@H Mobile Monitor Part 4 - Tunneling Madness
  5. Folding supports research into the cause of and potential Cures for Cancer, Neurological and Infectious Diseases. It is a way we can contribute back and honor the memory of those we've lost to these diseases. So who do you fold for?
  6. 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
  7. 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.
  8. 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 ?
  9. 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.
  10. 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!
  11. 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
  12. 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)
  13. 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
  14. 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.
  15. From the album: Briggsy public stuff

    proof that folding can be done with a hodge podge of cards. it takes a lot of tinkering and finding the right combination of drivers and monitor outputs, but it can be done... just don't ask me how because YMMV

    © Briggsy

  16. IMPORTANT EDIT: Link to my website is incorrect as I am migrating to a new datacentre! Hi all! It's been a while, but boy have I been busy! Over the last few months, I have acquired my own server! A HP ProLiant DL380 G6 to be precise. While I will post about that separately, here I would like to show you just one of the things I am doing with it. Scientific research! I am using Folding@Home and BOINC to allow my server to do computing for the greater good of mankind. To join my World Community Grid team, click here to visit my website to take you to the appropriate links. (Please be aware that my website is unfinished) Thanks for reading!
  17. From the album: Pics for Posts

    Peter_Purves LTT folding team member takes first place among the team, passing Anonymous1957 after a little over a year folding for LTT
  18. From the album: Pics for Posts

    Linus Tech Tips folding team member Peter_Purves is almost #1 in total points, June 29, 2016, from extremeoverclocking.com
  19. petem

    Workunits

    From the album: Pics for Posts

    Location of Work Units qty on the Stanford stats page.
  20. petem

    SeeStatsPic

    From the album: Pics for Posts

    How to find your WU's - click on the link on your webcontrol to go to the Stanford site.
  21. From the album: Grab bag

    As the title says, this pic is the Extremoverclocking page showing PrimalNaCl's new spot at the top of the LTT folding team with over 303M points.
  22. From the album: Grab bag

    Low cost Best in Class folding GPUs, with similar performing cards listed for comparison purposes
  23. From the album: Pics for Posts

    2 days from 12th place for Team Linus.
  24. From the album: Pics for Posts

    Linus Tech Tips team 2.8 days away from 12th spot in team rankings!
  25. From the album: Pics for Posts

    Linus Tech Tips team 3.8 days away from 12th spot in team rankings!
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