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ImportError
Windows 10 LTSC
chia-gigahorse-farmer-1.6.2.giga7-windows
after run start_farmer.cmd
1.6.2.giga4 "chia plots check" found one bad plot: <class 'RuntimeError'>: quick matching resulted in no matches error in getting challenge qualities for plot /data1/plot-k34-c6...
Running "chia plots check" found one bad plot here:
378 2023-02-19T07:56:36.712 chia.plotting.check_plots : ERROR <class 'RuntimeError'>: quick matching resulted in no matches error in getting challenge qualities for plot /data1/plot-k34-c6-2
378 023-02-18-09-04-.plot
379 2023-02-19T07:56:36.712 chia.plotting.check_plots : ERROR Proofs 23 / 30, 0.7667
Despite this error it still reports "Proofs 23/30" for this K34/C6 plot.
The other K34/Cx are fine.
Is this another "can happen"?
Is that plot still valuable for farming or should it be deleted (and recreated)?
More Info:
cat -n chia-plots-check-k34-one-bad-plot.txt |grep -v -e key -e address
1 .
2 [@4c527227c062 ~]$ ./chia plots check -g k34
3 2023-02-19T07:54:59.101 chia.plotting.check_plots : INFO Loading plots in config.yaml using plot_manager loading code (parallel read: True)
4
5 2023-02-19T07:54:59.274 chia.plotting.check_plots : INFO event: started, loaded 0 plots, 354 remaining
6 2023-02-19T07:54:59.275 chia.plotting.manager : INFO Only loading plots that contain "k34" in the file or directory name
7 2023-02-19T07:54:59.295 chia.plotting.check_plots : INFO event: batch_processed, loaded 7 plots, 54 remaining
8 2023-02-19T07:54:59.295 chia.plotting.manager : INFO Only loading plots that contain "k34" in the file or directory name
9 2023-02-19T07:54:59.297 chia.plotting.check_plots : INFO event: batch_processed, loaded 0 plots, 0 remaining
10 2023-02-19T07:54:59.297 chia.plotting.check_plots : INFO event: done, loaded 7 plots, 0 remaining
11 2023-02-19T07:54:59.307 chia.plotting.cache : INFO Saved 14073 bytes of cached data
12 2023-02-19T07:55:00.309 chia.plotting.check_plots : INFO
13 2023-02-19T07:55:00.309 chia.plotting.check_plots : INFO
14 2023-02-19T07:55:00.309 chia.plotting.check_plots : INFO Starting to test each plot with 30 challenges each
15
16 2023-02-19T07:55:00.309 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c1-2023-02-18-07-40-.plot k=34
19 [chiapos] Using 16 / 80 CPU threads
20 [chiapos] Using 2 / 2 CUDA devices
21 2023-02-19T07:55:00.705 chia.plotting.check_plots : INFO Looking up qualities took: 390 ms.
22 2023-02-19T07:55:01.085 chia.plotting.check_plots : INFO Finding proof took: 380 ms
23 2023-02-19T07:55:01.086 chia.plotting.check_plots : INFO Looking up qualities took: 0 ms.
24 2023-02-19T07:55:01.447 chia.plotting.check_plots : INFO Finding proof took: 361 ms
...
83 2023-02-19T07:55:12.832 chia.plotting.check_plots : INFO Proofs 31 / 30, 1.0333
84 2023-02-19T07:55:12.833 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c2-2023-02-18-07-57-.plot k=34
87 2023-02-19T07:55:12.948 chia.plotting.check_plots : INFO Looking up qualities took: 108 ms.
88 2023-02-19T07:55:13.332 chia.plotting.check_plots : INFO Finding proof took: 383 ms
...
166 2023-02-19T07:55:29.331 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c3-2023-02-18-08-14-.plot k=34
169 2023-02-19T07:55:29.383 chia.plotting.check_plots : INFO Looking up qualities took: 43 ms.
170 2023-02-19T07:55:29.813 chia.plotting.check_plots : INFO Finding proof took: 430 ms
...
208 2023-02-19T07:55:38.099 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c4-2023-02-18-08-30-.plot k=34
211 2023-02-19T07:55:38.169 chia.plotting.check_plots : INFO Looking up qualities took: 56 ms.
212 2023-02-19T07:55:38.647 chia.plotting.check_plots : INFO Finding proof took: 479 ms
...
280 2023-02-19T07:55:55.864 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c5-2023-02-18-08-47-.plot k=34
283 2023-02-19T07:55:55.990 chia.plotting.check_plots : INFO Looking up qualities took: 118 ms.
284 2023-02-19T07:55:56.616 chia.plotting.check_plots : INFO Finding proof took: 625 ms
...
328 2023-02-19T07:56:11.186 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c6-2023-02-18-09-04-.plot k=34
331 2023-02-19T07:56:11.501 chia.plotting.check_plots : INFO Looking up qualities took: 290 ms.
332 2023-02-19T07:56:12.409 chia.plotting.check_plots : INFO Finding proof took: 908 ms
...
375 2023-02-19T07:56:34.990 chia.plotting.check_plots : INFO Looking up qualities took: 407 ms.
376 2023-02-19T07:56:35.813 chia.plotting.check_plots : INFO Finding proof took: 822 ms
377 2023-02-19T07:56:35.813 chia.plotting.check_plots : INFO Looking up qualities took: 0 ms.
378 2023-02-19T07:56:36.712 chia.plotting.check_plots : ERROR <class 'RuntimeError'>: quick matching resulted in no matches error in getting challenge qualities for plot /data1/plot-k34-c6-2023-02-18-09-04-.plot
379 2023-02-19T07:56:36.712 chia.plotting.check_plots : ERROR Proofs 23 / 30, 0.7667
...
380 2023-02-19T07:56:36.712 chia.plotting.check_plots : INFO Testing plot /data1/plot-k34-c7-2023-02-18-09-21-.plot k=34
383 2023-02-19T07:56:37.354 chia.plotting.check_plots : INFO Looking up qualities took: 634 ms.
384 2023-02-19T07:56:38.980 chia.plotting.check_plots : INFO Finding proof took: 1625 ms
438 2023-02-19T07:57:27.667 chia.plotting.check_plots : INFO Summary
439 2023-02-19T07:57:27.667 chia.plotting.check_plots : INFO Found 6 valid plots, total size 1.95764 TiB
440 2023-02-19T07:57:27.667 chia.plotting.check_plots : INFO 6 plots of size 34
441 2023-02-19T07:57:27.668 chia.plotting.check_plots : WARNING 1 invalid plots found:
442 2023-02-19T07:57:27.668 chia.plotting.check_plots : WARNING 1 bad plots:
443 2023-02-19T07:57:27.668 chia.plotting.check_plots : WARNING /data1/plot-k34-c6-2023-02-18-09-04
Log file of creation does not show anything unusual.
Note: I am using S3 fpr creation as it is harvesting at the same time.
396 Calling ./cuda_plot_k34_ddb290d -c -f -t ./ -r 2 -C 6 -S 3
397 Chia k34 next-gen CUDA plotter - e161e4b
398 Plot Format: mmx-v2.4
399 Network Port: 8444 [chia]
400 No. GPUs: 2
401 No. Streams: 3
402 Final Destination: ./
403 Shared Memory limit: unlimited
404 Number of Plots: 1
405 GPU[0] cudaDevAttrConcurrentManagedAccess = 1
406 GPU[1] cudaDevAttrConcurrentManagedAccess = 1
407 Initialization took 0.224 sec
408 Crafting plot 1 out of 1 (2023/02/18 09:04:21)
409 Process ID: 6342
410 Pool Puzzle Hash:
411 Farmer Public Key:
412 Working Directory: ./
413 Working Directory 2: @RAM
414 Compression Level: C6 (xbits = 10, final table = 3)
415 Plot Name: plot-k34-c6-2023-02-18-09-04-
416 [P1] Setup took 1.436 sec
417 [P1] Table 1 took 77.191 sec, 17179869184 entries, 16792522 max, 17005 tmp, 0 GB/s up, 2.33193 GB/s down
418 [P1] Table 2 took 54.497 sec, 17179389547 entries, 16791126 max, 16984 tmp, 2.64235 GB/s up, 4.77098 GB/s down
419 [P1] Table 3 took 131.403 sec, 17178402609 entries, 16788983 max, 16993 tmp, 1.58287 GB/s up, 3.95732 GB/s down
420 [P1] Table 4 took 103.996 sec, 17176670599 entries, 16788301 max, 16975 tmp, 3.23062 GB/s up, 5.57718 GB/s down
421 [P1] Table 5 took 73.832 sec, 17173131561 entries, 16782556 max, 16971 tmp, 4.55002 GB/s up, 6.77218 GB/s down
422 [P1] Table 6 took 73.795 sec, 17166069104 entries, 16776795 max, 16949 tmp, 3.68444 GB/s up, 5.6915 GB/s down
423 [P1] Table 7 took 28.907 sec, 17151907180 entries, 16762143 max, 16991 tmp, 7.18971 GB/s up, 7.61075 GB/s down
424 Phase 1 took 545.743 sec
425 [P2] Setup took 1.038 sec
426 [P2] Table 7 took 8.705 sec, 14.6803 GB/s up, 0.244113 GB/s down
427 [P2] Table 6 took 8.266 sec, 15.4727 GB/s up, 0.257077 GB/s down
428 [P2] Table 5 took 8.489 sec, 15.0724 GB/s up, 0.250324 GB/s down
429 [P2] Table 4 took 8.7 sec, 14.7099 GB/s up, 0.244253 GB/s down
430 Phase 2 took 36.299 sec
431 [P3] Setup took 1.045 sec
432 [P3] Table 3 LPSK took 27.677 sec, 13756951780 entries, 14706026 max, 14729 tmp, 2.96702 GB/s up, 8.6716 GB/s down
433 [P3] Table 3 NSK took 24.681 sec, 13756951780 entries, 13448378 max, 14729 tmp, 6.22932 GB/s up, 10.6213 GB/s down
434 [P3] Table 4 PDSK took 10.494 sec, 13859478100 entries, 13558402 max, 13771 tmp, 12.3977 GB/s up, 20.9647 GB/s down
435 [P3] Table 4 LPSK took 13.584 sec, 13859478100 entries, 13862494 max, 14371 tmp, 17.9977 GB/s up, 17.6681 GB/s down
436 [P3] Table 4 NSK took 14.457 sec, 13859478100 entries, 13552075 max, 14103 tmp, 10.714 GB/s up, 18.1326 GB/s down
437 [P3] Table 5 PDSK took 10.384 sec, 14122904276 entries, 13820857 max, 14040 tmp, 12.5265 GB/s up, 21.1868 GB/s down
438 [P3] Table 5 LPSK took 14.571 sec, 14122904276 entries, 14250954 max, 14763 tmp, 17.0163 GB/s up, 16.4713 GB/s down
439 [P3] Table 5 NSK took 15.838 sec, 14122904276 entries, 13805312 max, 14482 tmp, 9.96564 GB/s up, 16.5516 GB/s down
440 [P3] Table 6 PDSK took 10.517 sec, 14839033501 entries, 14513030 max, 14703 tmp, 12.363 GB/s up, 20.9189 GB/s down
441 [P3] Table 6 LPSK took 13.65 sec, 14839033501 entries, 15089905 max, 15628 tmp, 18.8456 GB/s up, 17.5827 GB/s down
442 [P3] Table 6 NSK took 17.089 sec, 14839033501 entries, 14506075 max, 15308 tmp, 9.70444 GB/s up, 15.3399 GB/s down
443 [P3] Table 7 PDSK took 12.084 sec, 17151907180 entries, 16778940 max, 16991 tmp, 14.541 GB/s up, 18.2062 GB/s down
444 [P3] Table 7 LPSK took 14.885 sec, 17151907180 entries, 17202825 max, 17842 tmp, 19.2323 GB/s up, 16.1239 GB/s down
445 [P3] Table 7 NSK took 17.965 sec, 17151907180 entries, 16762143 max, 17415 tmp, 10.6701 GB/s up, 14.5919 GB/s down
446 Phase 3 took 219.462 sec
447 [P4] Setup took 0.279 sec
448 [P4] total_p7_parks = 8374955
449 [P4] total_c3_parks = 1715190, 2385 / 2458 ANS bytes
450 Phase 4 took 17.549 sec, 7.28199 GB/s up, 4.4098 GB/s down
451 Total plot creation time was 819.42 sec (13.657 min)
452 Flushing to disk took 61.036 sec
453 1222.13user 698.78system 16:40.35elapsed 192%CPU (0avgtext+0avgdata 785110060maxresident)k
454 49048inputs+670755944outputs (10major+212891326minor)pagefaults 0swaps
455 Sat Feb 18 09:21:01 UTC 2023
These are file sizes:
-rw-r--r-- 1 428679 428679 377718537311 Feb 18 08:55 plot-k34-c1-2023-02-18-07-40-.plot
-rw-r--r-- 1 428679 428679 370924485192 Feb 18 09:12 plot-k34-c2-2023-02-18-07-57-.plot
-rw-r--r-- 1 428679 428679 364008829256 Feb 18 09:28 plot-k34-c3-2023-02-18-08-14-.plot
-rw-r--r-- 1 428679 428679 357118280651 Feb 18 09:45 plot-k34-c4-2023-02-18-08-30-.plot
-rw-r--r-- 1 428679 428679 350264085095 Feb 18 10:02 plot-k34-c5-2023-02-18-08-47-.plot
-rw-r--r-- 1 428679 428679 343426952593 Feb 18 10:19 plot-k34-c6-2023-02-18-09-04-.plot
-rw-r--r-- 1 428679 428679 332417577418 Feb 18 10:33 plot-k34-c7-2023-02-18-09-21-.plot
Invalid -r | --ndevices, not enough devices: 0
Hello,
I wanted to get some advice on driver issue maybe?
I am running on Ubuntu 22 with 128GB of ram, running a GTX 1070
~/chia-gigahorse-master/cuda-plotter/linux/x86_64$ ./cuda_plot_k32 -n 3 -C 7 -t /media/plotter/nvme2/temp -2 /media/plotter/nvme0/temp -d /media/plotter/exos12tb11/plots/compressed -d /media/plotter//exos12tb31/plots/compressed -d /media/plotter/exos12tb81/plots/compressed -c <key_c> -f <key_f>
Invalid -r | --ndevices, not enough devices: 0
This is the driver I use.
CPU is intel 13600k, so with integrated graphic but i tried -g 0 or -g 1 or -g 2 but does not change anything.
Would you know where this could be coming from?
Clarification Request: VRAM Requirements
Is "When you mix different K size and C levels, only the highest RAM / VRAM requirement will apply." meant to, as a conservative measure, apply only to the calculation of max farm size using the table OR is it saying that the farmer will consume resources for all plots within a mix demand the same resources as the higher-compressed plots? I assume the former. I.e. if I have 60% C7 plots and 40% C8 plots, the resources required will be some prorated amount between C7 and C8, correct?
How to set environment variables under win10?
Why is it invalid to set environment variables under win10? How to turn off the GPU in win10?
set CHIAPOS_MAX_CUDA_DEVICES=0
setx CHIAPOS_MAX_CUDA_DEVICES 0
Tried both, nothing changed
ProofofSpace "-q" quiet option
Would it be possible to add a quiet option ProofofSpace?
When we run it with "check" option against a big folder, the current output is kind of overwhelming. On the other hand, the only intention is to see potential errors.
chia start farmer fails if the cwd is not set to gigahorse's directory
Plot with cuda ploter does not work i get an error request
Hi MadMax,
i want test your new gpu cuda ploter but it does not work.
my system is windows 10 with Ryzen9 5900x 64 GB DDR4 RAM & a RTX 3070 grafic card
i use the fellow parameters:
cuda_plot_k32.exe -n 1 -C 7 -t T:\ -3 T:\TEMP -d C:\HDD\FARM\ -M 64 -f ************* -c ***************
prety standard i guess..
but i come some issue request:
Invalid -r | --ndevices, not enough devices: 0
What did i do wrong? the drivers for the device i alway renew and all drivers are install..
Thank you for the help..
ByeBye
WOW
Small clarification on farm size
Just a small suggestion for the readme for the max farm size estimator. Could you just add a small line to confirm how to calculate the size of the farm to be compared with the max size.
Let's say you have c7 and 100 hundred plots. Is farm size in TB, 75 * 100 / 1024 or /1000 (just wanted to confirm we take compressed plots size and not uncompressed)
Log location for gigahorse
Hi Max,
could you let me know where are the logs for the farming/harvesting/node?
I would like to check if it works properly or not.
I just see:
chia_harvester: started
chia_farmer: started
chia_full_node: started
chia_wallet: started
Thanks!
Unsupported 16-Bit Application in Windows 10 x64 22H2
I am just testing this out in Windows currently as I only have 64GB of RAM and not sure of speeds, but if I try and run this I get this error immediately, even without any arguments.
I have unblocked the app via properties.
I get the same error on other K versions such as K33.
Unsupported 16-Bit Application
The program or feature "??\C:\gigahorse_plot\cuda_plot_k32.exe" cannot start or run due to incompatibity with 64-bit versions of Windows. Please contact the software vendor to ask if a 64-bit Windows compatible version is available.
Cuda Plotter Crashes During P1
I'm having trouble getting the k32 cuda plotter working. As you can see from the command output below, it stops plotting after P1 Table 2 without any indication as to why. Is there a log file somewhere I can look at? I'm hoping this is simply user error. I've tried various memory levels to no avail. My E: drive is an M.2 NVMe 1TB drive and the F: drive is a 14TB HDD.
Here are my system specs:
- Intel Core i7-10700K 3.8 GHz 8-Core Processor
- Nvidia 3080 Ti Founders Edition
- Corsair Dominator Platinum RGB 32 GB (2 x 16 GB) DDR4-3200 CL16 Memory
C:\Users\shahe\Documents\GitHub\chia-gigahorse\cuda-plotter\windows>.\cuda_plot_k32.exe -n 1 -t E:\Chia\ -d F:\Chia\ -f a672xxx -c xch1xxx -M 8
Chia k32 next-gen CUDA plotter - 15133ec
Plot Format: mmx-v2.4
Network Port: 8444 [chia]
No. GPUs: 1
No. Streams: 4
Final Destination: F:\Chia\
Shared Memory limit: 5.7 GiB
Number of Plots: 1
Initialization took 0.169 sec
Crafting plot 1 out of 1 (2023/02/10 22:33:41)
Process ID: 7120
Pool Puzzle Hash: f17450d617e4386c6106bdaedc8ec08c9ba8398ef12877909adc5d640a7f6b15
Farmer Public Key: a672xxx
Working Directory: E:\Chia\
Working Directory 2: @RAM
Compression Level: C1 (xbits = 15, final table = 3)
Plot Name: plot-k32-c1-2023-02-10-22-33-4a34eda13d95ef4fd882f9be5a2bbc47be8f7b515fd4fbeb5071605ef9e6f12f
[P1] Setup took 0.357 sec
[P1] Table 1 took 48.173 sec, 4294967296 entries, 16790172 max, 66650 tmp, 0 GB/s up, 0.705795 GB/s down
[P1] Table 2 took 447.948 sec, 4294838426 entries, 16785595 max, 66679 tmp, 0.0714369 GB/s up, 0.113853 GB/s down
C:\Users\shahe\Documents\GitHub\chia-gigahorse\cuda-plotter\windows>
Increase HDD write speed
There is a suggestion how to increase the recording speed on HDD.
Make two working dir -t -t1 for load balancing and alternate them in turn, this will make it possible to quickly copy on HDD
I have time PLOT 1.7 min. and I do not have time to copy it immediately at 8 HDD because -t is almost always busy 100%
For example:
-t /mnt/ssd1/ -t1 /mnt/ssd2/ ....
On ssd1 make 10 plots, then switch to ssd2 and also make 10 plots
This would give time to unload the ssd cache.
The first 5-10 sections are copied at a speed of 300-800mb/s, after 15-20plots the speed drops to 50-90mb/s. I don't know what it is, but adding -t1 solution would solve this problem as well.
Boosting plot-sink priority
I would suggest that plot-sink should have priority boosted over the one used by the cuda plotter. Plot-sink is basically an idle process that from time to time needs to get some data to be written to HDs. When there are no xfrs, it basically sits somewhere deep in the top processes list. When it is busy, it draws ~2% of a single core. So, the impact of such boost would have minimal if at all effect on the plotter or the box.
On the other hand, in case plot-sink gets behind (sitting on the same box as the plotter), it starts choking on HD writes, thus causing plotter to fill up the -t drive and work in start / stop fashion waiting for plot-sink to catch up (what from my observations never happens).
My box (Dell t7610, single 2695 v2, 256 GB 1,866 RAM, 3060 ti, Ubuntu 22:10) really suffered like that a lot. Therefore, I started to "renice -n -1" plot-sink, and it helped a lot. Even with that boosted priority, plot-sink is rarely on the 2 place in the top list. Also, plot times are basically exactly the same (~175 secs) as without boosting priority, but the start / stops are mostly gone when using 4 target drives (4 target drives means 4 plots, so roughly 12 mins, what is way too much for some reason).
My take is that if there is a way to boost reads from -t (over writes), that would further improve performance of this combo on a single box with just 256 GB RAM, as actually the HD writes can suppress the plotting max speed by introducing those extra stops.
Chia wallet show don't look in root-path
Hello. I install the node to run with compressed plots. I migrate .chia and .chia_folders from another node and place them not in the home directory.
I set --root-path and --keys-root-path but it seems binary still tries to use the home directory.
/home/yan/chia-gigahorse-farmer/chia.bin --root-path /mnt/nvme/.chia/mainnet --keys-root-path /mnt/nvme/.chia_keys/
can't find /home/yan/.chia/mainnet/config/config.yaml
** please run `chia init` to migrate or create new config files **
Exception ignored in: <compiled_async_generator object get_any_service_client at 0x564681e24ff0>
Traceback (most recent call last):
File "/home/yan/chia-gigahorse-farmer/asyncio/base_events.py", line 511, in _asyncgen_finalizer_hook
AttributeError: '_UnixSelectorEventLoop' object has no attribute '_asyncgens'
But most of the other's commands work as well with new path.
/home/yan/chia-gigahorse-farmer/chia.bin --root-path /mnt/nvme/.chia/mainnet --keys-root-path /mnt/nvme/.chia_keys/ start farmer
chia_harvester: started
chia_farmer: started
chia_full_node: started
chia_wallet: started
When can GPU computing be transferred from harvester machine to farmer machine๏ผ
My configuration of multiple harvesters is low. If I can transfer the calculation to the farmer machine, I can start plot C8 from now on, so as to transfer all to Gigahorse Compressed Plots.
GPU farming on Nvidia only?
Hello Max,
thanks for the awesome work.
I just wanted to ask as it seems that plotting needs cuda and Nvidia GPU.
Is it the same for farming? or does Amd work too there?
If Nvidia only, is it the same as for plotting in regards to generations gtx 1xxx and above?
Thank you
Error during synchronization
When I start the farmer, I can't sync up.
Deleting the db folder, running only the Node separately did not bring any results
My logs:
2023-02-11T00:15:33.864 wallet chia.wallet.wallet_node : WARNING Peer None did not respond in time.
2023-02-11T00:15:33.864 wallet wallet_server : WARNING Banning 95.165.27.175 for 120 seconds
2023-02-11T00:15:33.864 wallet chia.wallet.wallet_node : WARNING Peer None did not respond in time.
2023-02-11T00:15:33.864 wallet wallet_server : WARNING Banning 95.165.27.175 for 120 seconds
2023-02-11T00:15:33.869 wallet chia.wallet.wallet_node : WARNING Peer None did not respond in time.
2023-02-11T00:15:33.869 wallet wallet_server : WARNING Banning 86.158.16.140 for 120 seconds
2023-02-11T00:16:21.352 full_node chia.full_node.full_node: WARNING Not syncing, no peers with header_hash 5c06676beca06d4eea82cf5537fe26855c977bcbd9f836a465c3942f4b2fbe43
2023-02-11T00:16:21.353 full_node chia.full_node.full_node: ERROR failed fetching 2720 to 2752 from peers
2023-02-11T00:16:21.353 full_node chia.full_node.full_node: ERROR sync from fork point failed err: cannot schedule new futures after shutdown
2023-02-11T00:17:01.206 full_node chia.full_node.full_node: WARNING querying DNS introducer failed: The DNS response does not contain an answer to the question: dns-introducer.chia.net. IN A
Error: start failed
System: Ubuntu 20.04, x86_64.
Preparation:
wget https://github.com/madMAx43v3r/chia-gigahorse/releases/download/v1.6.2.giga7/chia-gigahorse-farmer-1.6.2.giga7-x86_64.tar.gz
tar zxf chia-gigahorse-farmer-1.6.2.giga7-x86_64.tar.gz
sudo apt install libgomp1 ocl-icd-opencl-dev
rm -rf ~/.chia
cd chia-gigahorse-farmer/
./chia.bin init
Then, I run ./chia.bin start farmer and get the following errors:
chia_harvester: chia_harvester failed to start. Error: start failed
chia_farmer: chia_farmer failed to start. Error: start failed
chia_full_node: chia_full_node failed to start. Error: start failed
chia_wallet: chia_wallet failed to start. Error: start failed
Antivirus Kaspersky detected virus in node mmx_node.exe
Kaspersky Antivirus detected mmx_node.exe as Trojan.Win32.Generic, virustotal.com - as malicious file!
Gigahorse node 0.9.9 windows, after restarting node and connected to peers Kaspersky stoped it and inform about virus.
Recover fresh mmx_node.exe and antivirus file scanning result is ok, untill I started node again, after first connections it blocked again.
Please set Giga compatible with other currencies!
Since giga can support xch's farmland, can you update it and mine xfx hdd stor stai sit xcf gbtc? It can bring certain benefits to miners!
I have been using giga's c8, but the income is not high. There is at least 10% revenue distance from NOSSD. I want to increase my income by mining other Chia's counterfeit coins!
Thank you for your efforts!
Multiple GPU plotting on Multi socket systems
Anyway we can get a bit more detialed on how to implement plotting using multiple GPUs on a multi socket systems?
numactl -N 0 -m 0 ./cuda_plot_k32 -g 0 ...
numactl -N 1 -m 1 ./cuda_plot_k32 -g 1 ...
This doesn't quite explain it to me. I've tried the command with this arugment numerous different ways and when the process does start it always dies out around [P1] Table 3 or 4.
For example:
./cuda_plot_k32.exe numactl -N 0 -m 0 numactl -N 1 -m 1 -g 1 -r 2 -n -1 -C 8 -x 8444 -M 256
Am I even looking at this the right way? I dont pretend to be fluent in script but normally I can figure some simple stuff out.
Dell T7610
Windows 10 Pro
Dual E5-2670v2
Dual 3060 Ti FE
512GB 1866Mhz DDR3
[Enhancement added to make it work] Wrong destination drives used if chia_plot_sink_disable is used / cuda-plotter
cuda-ploter is using a round-robin for plot distribution. It works great if there is room on all destination drives, or some are already full.
However, when a drive is blocked by chia_plot_sink_disable, such destination is skipped, but the index is not advanced appropriately, thus the next destination drive is using (n+1) plots (n - number of drives in the row blocked by sink-disable.
Maybe a test for that file should be added to the same function that does checks for space availability, as that flow is working fine.
ProofofSpace
When might wild card be added?
C:\gpuplot>ProofOfSpace check -r 8 -f m:\mmxk33c*.plot
operation: check
Caught exception: Invalid file: m:\mmxk33c*.plot
farm chive plots
Where to get information to farm chive plots?
There is no information available for configuring gigahorse to plot chives.
On a machine with Chia installed, detection is automatic of Chia plots. However, there is no information to configure, point to the Chives folder with certificates, Pools, plots and etc.
Also, there is no information if it is possible to have two instances of gigahorse on the same machine, one for Chia and another for Chives, or if a single instance can farm everything together.
Can anyone provide info where to get answers to the above?
Farming questions
I have two questions when farming with this chia-gigahorse.
-
What is the reason for the farmer to be not compatible with the official Chia node? I have a large farm and it relies on tuning the setting of the Chia node to work with the infrastructure. From my understanding, the Chia node just deals with public data. I understand that you want to secure your fees. But transactions are created and signed by the farmer. You can simply compile the farmer into closed source. I have a node that is shared by many farmers. Running a node for each farmer is impractical for me.
-
Where do I set the farmer and pool target_addresses for receiving reward? Where do the block rewards go? Do you just assume that users would only use plotting keys for receiving rewards?? That is a huge security risks. For a farming business, the plotting keys should be regarded as public and not secure because any employee responsible for the maintenance can easily have access to it and we have to rely on setting target_addresses to a cold wallet address for security.
If these two problems cannot be resolved, we will have to stop plotting into this closed source farmer.
Node doesn't seem to sync due to to many cpu cores/threads reported by zstd
Hello, on a dual 64 core Epyc machine with a total of 255 CPU hyper threads, the zstd lib reports an error of bad thread count.. Below is running the gigahorse chia node. When I disable SMT, reducing the threads to 128 (via bios), then the nodes syncs fine. numactl/taskset only pin the process to CPU cores/threads but doesn't control how many threads zstd is seeing.
2023-02-24T00:05:02.563 full_node full_node_server : ERROR Exception: Bad threads count - more than 200: 255 <class 'zstd.Error'>, closing connection {'host': '193.72.52.204', 'port': 8444}. Traceback (most recent call last):
File "/home/srv_chia/chia-gigahorse-farmer/chia/server/server.py", line 634, in api_call
File "/home/srv_chia/chia-gigahorse-farmer/asyncio/tasks.py", line 494, in wait_for
File "/home/srv_chia/chia-gigahorse-farmer/chia/server/server.py", line 624, in wrapped_coroutine
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/full_node_api.py", line 1495, in respond_compact_vdf
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/full_node.py", line 2512, in respond_compact_vdf
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/full_node.py", line 2413, in _replace_proof
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/block_store.py", line 174, in replace_proof
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/block_store.py", line 137, in compress
zstd.Error: Bad threads count - more than 200: 255
2023-02-24T00:05:02.701 full_node full_node_server : WARNING Banning 193.72.52.204 for 10 seconds
2023-02-24T00:05:02.701 full_node full_node_server : INFO Connection closed: 193.72.52.204, node id: 295ea99968c526f843ad70159c3c739ad8fc81374675a1523ed3e4f5a87436b3
2023-02-24T00:05:02.701 full_node chia.full_node.full_node: INFO peer disconnected {'host': '193.72.52.204', 'port': 8444}
2023-02-24T00:05:02.702 full_node full_node_server : WARNING Banning 193.72.52.204 for 600 seconds
2023-02-24T00:05:02.703 full_node chia.full_node.full_node: ERROR Error with syncing: <class 'RuntimeError'>Traceback (most recent call last):
File "/home/srv_chia/chia-gigahorse-farmer/chia/full_node/full_node.py", line 1034, in _sync
RuntimeError: Weight proof did not arrive in time from peer: 193.72.52.204
plot copy tool often fails
The plot copy tool fails all the time with this errors :
send() failed with: Success (0)
connect() failed with: Network is unreachable (101)
on the receiving side:
then the files are deleted.
After it successfully copies a few plots it does it for the rest of the plots, I thought it might be a network issue but I tried a different NIC and switch with the same results I also tried https://github.com/maxbanton/chia-plot-mover and it doesn't seem to have these issues.
I would rather use the plot sync-copy tool since it seems way faster than the plot mover.
Edit: add more info
Plot filter
Is there a way to check the plot filter to see how many plots are passing filter, proofs found and such, like a command to type that will alow this to run so I can see this
chiapos/ProofOfSpace 12c9255: "lookup" only uses one GPU for multi-GPU setup, performance anomalies with CUDA_VISIBLE_DEVICES settings
Hi,
I wanted to test multi-GPU performance with "chiapos/ProofOfSpace lookup".
Actual behaviour: It uses only one GPU.
Even when setting "export CHIAPOS_MAX_CUDA_DEVICES=2" it still uses one GPU.
Expected behaviour: it should use all GPUs by default (or when setting CHIAPOS_MAX_CUDA_DEVICES).
Also there is a performance penalty when using CUDA_VISIBLE_DEVICES for only 1 GPU.
Details see below.
Am I missing something?
1) Default settings
===================
[root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 8 lookup -f plot-k33-c5-2023-02-13-16-22* >x
real 0m22.626s
user 0m7.164s
sys 0m3.371s
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 30% 55C P8 16W / 125W | 101MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 40% 59C P2 199W / 225W | 776MiB / 8192MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 277826 C ./ProofOfSpace_mmx_12c9255 98MiB |
| 1 N/A N/A 277826 C ./ProofOfSpace_mmx_12c9255 774MiB |
+-----------------------------------------------------------------------------+
Result: It uses 3060Ti with 100%, real=22sec.
2) export CHIAPOS_MAX_CUDA_DEVICES=2
=====================================
[root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 8 lookup -f plot-k33-c5-2023-02-13-16-22* >x
real 0m21.611s
user 0m7.369s
sys 0m1.873s
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 30% 60C P0 37W / 125W | 741MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 40% 63C P2 201W / 225W | 776MiB / 8192MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 277735 C ./ProofOfSpace_mmx_12c9255 738MiB |
| 1 N/A N/A 277735 C ./ProofOfSpace_mmx_12c9255 774MiB |
+-----------------------------------------------------------------------------+
Result: Same as run 1. But in addition it also allocates memory on RTX4000, but does not use GPU%.
3) Reverse CUDA ordering, so it uses RTX4000
============================================
[root@c19338cec46c data1]# export CUDA_VISIBLE_DEVICES=1,0
[root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 8 lookup -f plot-k33-c5-2023-02-13-16-22*backup >x
real 0m32.347s
user 0m7.612s
sys 0m3.264s
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 30% 66C P0 121W / 125W | 741MiB / 8192MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 40% 48C P2 67W / 225W | 136MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 278057 C ./ProofOfSpace_mmx_12c9255 738MiB |
| 1 N/A N/A 278057 C ./ProofOfSpace_mmx_12c9255 134MiB |
+-----------------------------------------------------------------------------+
Result: Now it uses RTX4000 at 100% GPU, real=32sec. It does not use 3060Ti.
4) Lower performance for CUDA_VISIBLE_DEVICES=1 (which should be equivalent to run (3))
[root@c19338cec46c data1]# export CUDA_VISIBLE_DEVICES=1
[root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 8 lookup -f plot-k33-c5-2023-02-13-16-22*backup >x
real 0m40.911s
user 0m7.750s
sys 0m1.480s
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 48% 76C P0 84W / 125W | 741MiB / 8192MiB | 23% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 30% 42C P0 60W / 225W | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 278404 C ./ProofOfSpace_mmx_12c9255 738MiB |
+-----------------------------------------------------------------------------+
Result: Now it uses RTX4000 at 23%, it runs slower with real=40sec
5) Also lower performance for CUDA_VISIBLE_DEVICES=0 (which should be same as run (1))
===========================================
[root@c19338cec46c data1]# export CUDA_VISIBLE_DEVICES=0
[root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 8 lookup -f plot-k33-c5-2023-02-13-16-22*backup >x
real 0m28.480s
user 0m7.578s
sys 0m3.417s
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 27% 55C P0 18W / 125W | 0MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 40% 54C P2 161W / 225W | 776MiB / 8192MiB | 40% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 1 N/A N/A 278841 C ./ProofOfSpace_mmx_12c9255 774MiB |
+-----------------------------------------------------------------------------+
Result: Now it uses 3060Ti at 40%, it runs slower with real=28sec.
6) Running without GPU, CPU is 2x Xeon 2698v4
=============================================
export CHIAPOS_MAX_CORES="80"
export CHIAPOS_MAX_CUDA_DEVICES="0"
root@c19338cec46c data1]# time ./ProofOfSpace_mmx_12c9255 -r 80 lookup -f plot-k33-c5-2023-02-13-16-22*backup >x
real 0m55.244s
user 51m12.735s
sys 0m31.537s
top output:
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
303755 gputest 20 0 39.0g 24.5g 9024 R 7875 2.4 6:34.19 ProofOfSpace_mm
Result: GPU is faster than this dual CPU for K33/C5
7)
I am using latest binary as of today:
[root@c19338cec46c data1]# md5sum ProofOfSpace_mmx_12c9255
201b230da0650ef13f396d920575ad39 ProofOfSpace_mmx_12c9255
plot-sink plot permissions
When copying to the Windows version of plot-sink, plots are created with permissions that do not allow them to be opened via network access. To solve this problem, you have to use takeown and icacls with SID *S-1-1-0 each time.
Is it possible to set up plot-sink so that access permissions are assigned automatically?
GPU Plotter Stalls
System: Ryzen 5800X ; 64 GB ; 2 TB PCIe3 NVME ("p:" below) ; GPU1: RX6800 (not used) ; GPU2: Tesla P4. ; OS: Win11.
Command: ......\cuda_plot_k32.exe -C 8 -n 1 -t p:\ -3 p:\ -d p:\ -c xxxxxxxxxxx -f xxxxxxxx -M 32
Problem: Plotter stalls on Phase 1 Table 3 or 4. GPU sometimes remains pegs at 100% or falls to 0%. NVME disk activity falls to zero. RAM remains pegged at โ63 of 64gb. No error messages displayed in plotter, plotter just stops. When restarting plotter, sometimes requires system restart to avoid error message of zero devices available.
Any ideas?
EDIT: The PCIe slot that the Tesla P4 is in runs at x4, not x16, if that makes a difference.
-3 is unavaliable
System: Ryzen 12400f ; 64 GB ; 1.92TB PCIe3 NVME ("p:" below) ; GPU1: Rtx3060ti (not used) ; OS: Win10.
Command: ......\cuda_plot_k32.exe -C 8 -n -1 -t p:\ -3 p:\ -d p:\ -c xxxxxxxxxxx -f xxxxxxxx -M 32
Problem: Plotter stalls on Phase 1,no cmd window remained,lt just dont work
cuda-plotter instance quits unexpected
cuda-plotter instance quits unexpectedly and the terminal window in which the command was initiated closes automatically very often on my linux plotting machine. I am using cuda_plot_k33 and 1/2 Partial RAM model. This generally happens towards the end of P3 or while the finished plot is being copied to the destination hard drive. It seems setting -n to -1 or any number larger than 1 almost always causes this problem while setting -n to 1 does not, although I noticed the following message while running the cuda-plotter: WritePark(): ans_length (846) > max_ans_length (845) (y = 1, i = 7899).
The linux plotting machine has an Intel Core-i9 10980XE CPU, 256 GB DDR4 RAM, 2x NVIDIA RTX A6000 (only one GPU is used for plotting), 2x NVIDIA Titan V. -2 is RAID 0 of 2x Optane 905p.
Any suggestions to fix this issue? Thanks a lot!
Cuda ploter -S (stream) param always = 3
-S param value is not efffective, always get maximum streams = 3 with nvidia 4090 (mmx plots, linux)
Chia k32 next-gen CUDA plotter - c892fce
Plot Format: mmx-v2.4
Network Port: 11337 [MMX] (unique)
No. GPUs: 1
No. Streams: 3
Plots showing as active and farming on the gigahorse-farmer, but not the pool.
Hey, so after i got all of my 497 compressed plots ready for pooling, I noticed something strange. All of the plots passed validation and were being noticed by the farmer, but I was getting no points and the pool was showing nothing for my launcher id. I checked and made sure that all of the info/settings that were inputted were correct, and they were.
Problem with plots
Failure to farm compressed plots with chia-gigahorse-farmer and spacepool NFT
Hello,
I'm trying to farm K32 C8 compressed plots created with chia-gigahorse with gigahorse-farmer against an NFT in spacepool. I'm having issues where the gigahorse-farmer doesnt seem to see my plots if I run the ./chia.bin plotnft show. It also seems to have issues to retrieve information for spacepool NFT.
Output from my standard chia client - all looking good.
(venv) pi@raspberrypi-chia:~/chia-blockchain $ chia plotnft show
Wallet height: 3367818
Sync status: Synced
Wallet id 2:
Current state: FARMING_TO_POOL
Current state from block height: 547628
Launcher ID: XXX
Target address (not for plotting): XXX
Number of plots: 929
Owner public key: XXX
Pool contract address (use ONLY for plotting - do not send money to this address): XXX
Current pool URL: https://asia1.pool.space
Current difficulty: 19
Points balance: 2872
Points found (24h): 9253
Percent Successful Points (24h): 100.00%
Payout instructions (pool will pay to this address): XXX
Relative lock height: 64 blocks
Wallet id 3:
Current state: FARMING_TO_POOL
Current state from block height: 3367799
Launcher ID: XXX
Target address (not for plotting): XXX
Number of plots: 0
Owner public key: XXX
Pool contract address (use ONLY for plotting - do not send money to this address): XXX
Current pool URL: https://xch-sg.flexpool.io
Current difficulty: 1
Points balance: 9999
Points found (24h): 0
Percent Successful Points (24h): 0.00%
Payout instructions (pool will pay to this address): XXX
Relative lock height: 100 blocks
Output for the same wallet with chia-gigahorse-farmer. You can see that the ouput for wallet id 2 is truncated.
root@60dd68783711:/home/chia-gigahorse-farmer# ./chia.bin plotnft show
Wallet height: 3367803
Sync status: Synced
Wallet id 2:
Current state: FARMING_TO_POOL
Current state from block height: 547628
Launcher ID: XXX
Target address (not for plotting): XXX
Number of plots: 0
Owner public key: XXX
Pool contract address (use ONLY for plotting - do not send money to this address): XXX
Current pool URL: https://asia1.pool.space
Relative lock height: 64 blocks
Wallet id 3:
Current state: FARMING_TO_POOL
Current state from block height: 3367799
Launcher ID: XXX
Target address (not for plotting): XXX
Number of plots: 0
Owner public key: XXX
Pool contract address (use ONLY for plotting - do not send money to this address): XXX
Current pool URL: https://xch-sg.flexpool.io
Current difficulty: 1
Points balance: 9999
Points found (24h): 0
Percent Successful Points (24h): 0.00%
Payout instructions (pool will pay to this address): XXX
Relative lock height: 100 blocks
Is chia-gigahorse-farmer capable of running with any pool?
Chiapos plot check results
What result value should be good for mmx plots?
Does it mean that > 100% result more lucky plot to find blocks?
cuda_plot_k32 v2.0.0-e161e4b crashes on single Ctrl+c
Ubuntu 22:10; single e5-2695 v2, 256 GB RAM, 3060 Ti, k32 / C8 plots
It happened to me already twice with the latest plotter / sink. I did a single Ctrl+c on plotter to have gracefully end, but it immediately terminated connection to plot_sink, sit idle for several seconds, and aborted. There were no error messages coming from the plotter. On the other hand, plot-sink killed pending xfrs; however, it appears to be waiting for new jobs (so plot-sink is sound).
In case it matters where the plotter was in the process, it just started phase 3 and spit out the first [P3] line.
Output from the plot-sink:
Started copy to /mnt/d3/mmx/plots/plot-mmx-k32-c8-2023-02-09-20-55-07393b1a764ac050b18c1f20a003aac6bb998128c9bf9a9153165a8ac1e74b9d.plot (71.2455 GiB)
recv() failed with: EOF
recv() failed with: EOF
recv() failed with: EOF
recv() failed with: EOF
Deleted /mnt/d3/mmx/plots/plot-mmx-k32-c8-2023-02-09-20-55-07393b1a764ac050b18c1f20a003aac6bb998128c9bf9a9153165a8ac1e74b9d.plot.tmp
Deleted /mnt/d2/mmx/plots/plot-mmx-k32-c8-2023-02-09-20-52-356e1890c30f9ee81468475623e836e5ba1d018a39b4f9e13d6f9e5837eb52fb.plot.tmp
Deleted /mnt/d1/mmx/plots/plot-mmx-k32-c8-2023-02-09-20-49-55cfa309baab5a50ba846ac192c697f9e8fa93edc801d79d5bfa96eb68f11789.plot.tmp
Deleted /mnt/d4/mmx/plots/plot-mmx-k32-c8-2023-02-09-20-46-6f60aee4fb1bfe4e981c82e5bb5e52bd2285effe79de22b72ac24cde1b2a9659.plot.tmp
In both cases the plotter / sink combo was running for few long hours. It looks to me that this is a newly introduced problem.
By the way, could you add --version to plot-sink. Right now, instead of version, it prints --help.
How do I farm with GPU? Is there a tutorial?
I see it is mentioned that the compressed plots can be farmed by GPU, but there is no tutorial on exactly how to do it. Since currently most computation is done on harvesters and there can be many harvesters, it will ideally be done by low-end GPUs. However, there is not information on what kind of GPU (e.g. GPU memory requirement, frequency and cores) is required for the farming. It will be helpful to have some information about this to set up an efficient farm.
cuda_plot c892fce K34 C8: what(): invalid argument, signal 6, NVRM MMU Fault: ENGINE GRAPHICS GPCCLIENT_T1_2 faulted ...FAULT_PTE ACCESS_TYPE_VIRT_READ and park_delta(): LP_1 < LP_0 (0, 142975494547708) and park_delta_split(): stub_bits > MAX_STUB_BITS (228)
Trying to plot k34c8 I get these errors.
Using latest version:
53008f3e7d1d38ab79503f0085be1dbe cuda_plot_k34_3afd79e
Chia k34 next-gen CUDA plotter - c892fce
1) Dual GPU:
370 Sun Feb 19 11:53:18 UTC 2023
371 53008f3e7d1d38ab79503f0085be1dbe cuda_plot_k34_3afd79e
372 Calling ./cuda_plot_k34_3afd79e -c -f -t ./ -C 8 -r 2 -S 2
373 Chia k34 next-gen CUDA plotter - c892fce
374 Plot Format: mmx-v2.4
375 Network Port: 8444 [chia]
376 No. GPUs: 2
377 No. Streams: 2
378 Final Destination: ./
379 Shared Memory limit: unlimited
380 Number of Plots: 1
381 GPU[0] cudaDevAttrConcurrentManagedAccess = 1
382 GPU[1] cudaDevAttrConcurrentManagedAccess = 1
383 Initialization took 0.441 sec
384 Crafting plot 1 out of 1 (2023/02/19 11:53:20)
385 Process ID: 3697
386 Pool Puzzle Hash:
387 Farmer Public Key:
388 Working Directory: ./
389 Working Directory 2: @RAM
390 Compression Level: C8 (xbits = 8, final table = 4)
391 Plot Name: plot-k34-c8-2023-02-19-11-53-
392 [P1] Setup took 1.106 sec
393 [P1] Table 1 took 95.071 sec, 17179869184 entries, 16792237 max, 16997 tmp, 0 GB/s up, 1.89336 GB/s down
394 [P1] Table 2 took 61.652 sec, 17179482210 entries, 16790487 max, 16998 tmp, 2.33569 GB/s up, 4.21728 GB/s down
395 [P1] Table 3 took 105.75 sec, 17178537599 entries, 16788153 max, 16981 tmp, 1.96686 GB/s up, 3.97167 GB/s down
396 [P1] Table 4 took 133.255 sec, 17176843365 entries, 16787856 max, 17054 tmp, 2.52129 GB/s up, 4.35259 GB/s down
397 [P1] Table 5 took 94.097 sec, 17173319911 entries, 16784141 max, 16968 tmp, 3.57015 GB/s up, 5.31371 GB/s down
398 [P1] Table 6 took 82.544 sec, 17166101940 entries, 16775288 max, 16968 tmp, 3.29396 GB/s up, 5.08824 GB/s down
399 [P1] Table 7 took 28.057 sec, 17151856671 entries, 16762241 max, 17018 tmp, 7.40754 GB/s up, 7.84132 GB/s down
400 Phase 1 took 601.871 sec
401 [P2] Setup took 1.045 sec
402 [P2] Table 7 took 8.557 sec, 14.9341 GB/s up, 0.248335 GB/s down
403 [P2] Table 6 took 8.344 sec, 15.3281 GB/s up, 0.254674 GB/s down
404 [P2] Table 5 took 8.305 sec, 15.4065 GB/s up, 0.25587 GB/s down
405 Phase 2 took 27.233 sec
406 [P3] Setup took 0.723 sec
407 [P3] Table 4 LPSK took 17.612 sec, 13859485225 entries, 20910390 max, 20951 tmp, 7.38715 GB/s up, 13.6273 GB/s down
408 terminate called after throwing an instance of 'std::runtime_error'
409 what(): invalid argument
410 Command terminated by signal 6
411 713.76user 464.06system 12:45.28elapsed 153%CPU (0avgtext+0avgdata 660232484maxresident)k
412 800inputs+152outputs (2major+178170431minor)pagefaults 0swaps
413 Sun Feb 19 12:06:04 UTC 2023
This also logs this error (note: my TZ in container has 1h offset)
[Sun Feb 19 13:04:19 2023] NVRM: GPU at PCI:0000:84:00: GPU--
[Sun Feb 19 13:04:19 2023] NVRM: Xid (PCI:0000:84:00): 31, pid=556985, name=cuda_plot_k34_3, Ch 0000000a, intr 00000000. MMU Fault: ENGINE GRAPHICS GPCCLIENT_T1_2 faulted @ 0x7f0c_b8808000. Fault is of type FAULT_PTE ACCESS_TYPE_VIRT_READ
2) Single CPU shows this error:
365 Sun Feb 19 14:32:37 UTC 2023
366 53008f3e7d1d38ab79503f0085be1dbe cuda_plot_k34_3afd79e
367 Calling ./cuda_plot_k34_3afd79e -c -f -t ./ -C 8
368 Chia k34 next-gen CUDA plotter - c892fce
369 Plot Format: mmx-v2.4
370 Network Port: 8444 [chia]
371 No. GPUs: 1
372 No. Streams: 4
373 Final Destination: ./
374 Shared Memory limit: unlimited
375 Number of Plots: 1
376 Initialization took 0.303 sec
377 Crafting plot 1 out of 1 (2023/02/19 14:32:39)
378 Process ID: 34
379 Pool Puzzle Hash:
380 Farmer Public Key:
381 Working Directory: ./
382 Working Directory 2: @RAM
383 Compression Level: C8 (xbits = 8, final table = 4)
384 Plot Name: plot-k34-c8-2023-02-19-14-32-
385 [P1] Setup took 1.13 sec
386 [P1] Table 1 took 94.079 sec, 17179869184 entries, 16792288 max, 17023 tmp, 0 GB/s up, 1.91333 GB/s down
387 [P1] Table 2 took 65.149 sec, 17179493109 entries, 16789119 max, 17016 tmp, 2.21032 GB/s up, 3.99091 GB/s down
388 [P1] Table 3 took 105.42 sec, 17178732824 entries, 16788682 max, 17002 tmp, 1.97302 GB/s up, 3.9841 GB/s down
389 [P1] Table 4 took 140.61 sec, 17177127045 entries, 16788296 max, 16974 tmp, 2.38943 GB/s up, 4.12491 GB/s down
390 [P1] Table 5 took 96.826 sec, 17174131820 entries, 16783423 max, 17031 tmp, 3.46959 GB/s up, 5.16394 GB/s down
391 [P1] Table 6 took 86.193 sec, 17167749724 entries, 16777113 max, 17001 tmp, 3.15465 GB/s up, 4.87283 GB/s down
392 [P1] Table 7 took 36.825 sec, 17155275131 entries, 16765860 max, 17020 tmp, 5.64435 GB/s up, 5.97431 GB/s down
393 Phase 1 took 626.627 sec
394 [P2] Setup took 1.163 sec
395 [P2] Table 7 took 12.483 sec, 10.2393 GB/s up, 0.170232 GB/s down
396 [P2] Table 6 took 12.574 sec, 10.1726 GB/s up, 0.169 GB/s down
397 [P2] Table 5 took 12.492 sec, 10.2431 GB/s up, 0.170109 GB/s down
398 Phase 2 took 39.145 sec
399 [P3] Setup took 0.783 sec
400 [P3] Table 4 LPSK took 21.44 sec, 13860059704 entries, 20920766 max, 20975 tmp, 6.06831 GB/s up, 11.1942 GB/s down
401 park_delta(): LP_1 < LP_0 (0, 142975494547708) (x = 476, y = 8704)
402 park_delta_split(): stub_bits > MAX_STUB_BITS (228) (y = 8726)
403 park_delta_split(): stub_bits > MAX_STUB_BITS (243) (y = 8735)
404 park_delta_split(): stub_bits > MAX_STUB_BITS (251) (y = 8718)
405 park_delta_split(): stub_bits > MAX_STUB_BITS (207) (y = 8731)
406 park_delta_split(): stub_bits > MAX_STUB_BITS (226) (y = 8722)
407 park_delta_split(): stub_bits > MAX_STUB_BITS (206) (y = 8729)
408 park_delta_split(): stub_bits > MAX_STUB_BITS (223) (y = 8717)
409 park_delta_split(): stub_bits > MAX_STUB_BITS (293) (y = 8737)
410 park_delta_split(): stub_bits > MAX_STUB_BITS (245) (y = 8733)
411 park_delta_split(): stub_bits > MAX_STUB_BITS (262) (y = 8725)
412 park_delta_split(): stub_bits > MAX_STUB_BITS (245) (y = 8715)
413 park_delta_split(): stub_bits > MAX_STUB_BITS (240) (y = 8707)
414 park_delta_split(): stub_bits > MAX_STUB_BITS (215) (y = 8708)
415 park_delta_split(): stub_bits > MAX_STUB_BITS (206) (y = 8720)
416 park_delta_split(): stub_bits > MAX_STUB_BITS (237) (y = 8736)
417 park_delta_split(): stub_bits > MAX_STUB_BITS (211) (y = 8730)
418 park_delta_split(): stub_bits > MAX_STUB_BITS (255) (y = 8710)
419 park_delta_split(): stub_bits > MAX_STUB_BITS (189) (y = 8727)
420 park_delta_split(): stub_bits > MAX_STUB_BITS (219) (y = 8714)
421 park_delta_split(): stub_bits > MAX_STUB_BITS (234) (y = 8716)
422 park_delta_split(): stub_bits > MAX_STUB_BITS (179) (y = 8732)
423 park_delta_split(): stub_bits > MAX_STUB_BITS (241) (y = 8719)
424 park_delta_split(): stub_bits > MAX_STUB_BITS (201) (y = 8728)
425 park_delta_split(): stub_bits > MAX_STUB_BITS (267) (y = 8709)
426 park_delta_split(): stub_bits > MAX_STUB_BITS (206) (y = 8723)
427 park_delta_split(): stub_bits > MAX_STUB_BITS (266) (y = 8724)
428 park_delta_split(): stub_bits > MAX_STUB_BITS (234) (y = 8711)
429 park_delta_split(): stub_bits > MAX_STUB_BITS (254) (y = 8721)
430 park_delta_split(): stub_bits > MAX_STUB_BITS (231) (y = 8706)
431 park_delta_split(): stub_bits > MAX_STUB_BITS (244) (y = 8713)
432 park_delta_split(): stub_bits > MAX_STUB_BITS (243) (y = 8712)
433 park_delta_split(): stub_bits > MAX_STUB_BITS (253) (y = 8734)
434 terminate called after throwing an instance of 'std::runtime_error'
435 what(): invalid argument
436 Command terminated by signal 6
437 721.19user 458.59system 13:23.50elapsed 146%CPU (0avgtext+0avgdata 661050872maxresident)k
438 0inputs+160outputs (0major+182843801minor)pagefaults 0swaps
439 Sun Feb 19 14:46:01 UTC 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro RTX 4000 Off | 00000000:04:00.0 Off | N/A |
| 30% 47C P8 13W / 125W | 3MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:84:00.0 Off | N/A |
| 40% 60C P2 180W / 225W | 7970MiB / 8192MiB | 100% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 1 N/A N/A 582284 C ./cuda_plot_k34_3afd79e 7012MiB |
+-----------------------------------------------------------------------------+
Chia-gigahorse build for windows
Hello Max,
Can you tell me where can I download a ready-made build for windows?
Thank you
Running ProofOfSpace under win10, a strange prompt appears:
PS D:> Measure-Command {./ProofOfSpace lookup -r 8 -f plot-k32-c8-2023-02-27-13-05-24c464f26aa358db1bf2ddb1dd182e3abfe130c45512e6561ec1407e793d22e8.plot|Out-Default}
operation: lookup
[chiapos] Using 16 / 16 CPU threads
[chiapos] Using 1 / 1 CUDA devices
[chiapos] Using 2 / 2 OpenCL devices (AMD Accelerated Parallel Processing)
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: GPU recompute failed with: clEnqueueNDRangeKernel() failed for kernel 'kernel0' with CL_INVALID_CONTEXT
Threw: bad allocation
Threw: bad allocation
Threw: bad allocation
......
......
Cuda_plot windows drive mounted as folder
Using cuda_plot_k32.exe if a -d is a folder mounted drive it won't work and just gives a write permission error. It works just fine if the drive is letter mounted.
works:
cuda_plot_k32.exe -d D:\
broken:
cuda_plot_k32.exe -d C:\chia\14tb1\
Start error windows version gigahorse farmer
I installed this distribution (chia-gigahorse-farmer-1.6.2.giga7-windows.zip) on the Windows server. However, when I start, I get this error:
Is it possible to fix it somehow ?
Strange error in log
I just noticed my estimated plot size keep going down so I checked the log and found this error:
Good thing is everything is back to normal after restart
Gigahorse 1.6.2.giga4: harvester VRAM increase from 768MB to 1646MB for k33-c5
I see increase of harvester VRAM for k33-c5 plots:
| 0 N/A N/A 338900 C chia_harvester 768MiB |
Later
| 0 N/A N/A 338900 C chia_harvester 1646MiB |
The Readme does not mention that effect.
Currently this is not a problem, however I would like to know if k33-c8 (VRAM=5,766 for farming
according to readme) will work fine as only 8GB VRAM are available. I.e. will it also need for
double (triple?) the VRAM while harvesting or will it stay at VRAM from readme)?
Perhaps that is related to the "eligible" plots?
2023-02-19T20:56:58.775 harvester chia.harvester.harvester: INFO 3 plots were eligible for farming c7142e706f... Found 0 proofs. Time: 0.32562 s. Total 333 plots
...
2023-02-19T20:53:20.744 harvester chia.harvester.harvester: INFO 0 plots were eligible for farming ee742b48fb... Found 0 proofs. Time: 0.00468 s. Total 333 plots
2023-02-19T20:53:30.103 harvester chia.harvester.harvester: INFO 1 plots were eligible for farming ee742b48fb... Found 0 proofs. Time: 0.54548 s. Total 333 plots
2023-02-19T20:53:40.187 harvester chia.harvester.harvester: INFO 1 plots were eligible for farming c7142e706f... Found 0 proofs. Time: 0.02158 s. Total 333 plots
2023-02-19T20:53:49.663 harvester chia.harvester.harvester: INFO 2 plots were eligible for farming c7142e706f... Found 0 proofs. Time: 0.02830 s. Total 333 plots
2023-02-19T20:53:59.093 harvester chia.harvester.harvester: INFO 0 plots were eligible for farming c7142e706f... Found 0 proofs. Time: 0.00469 s. Total 333 plots
[@4c527227c062 ~]$ ./chia version
1.6.2.giga4
After starting harvester:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:2D:00.0 Off | N/A |
| 30% 44C P8 6W / 200W | 770MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Quadro RTX 4000 Off | 00000000:99:00.0 Off | N/A |
| 30% 46C P8 9W / 125W | 101MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 338900 C chia_harvester 768MiB |
| 1 N/A N/A 338900 C chia_harvester 98MiB |
+-----------------------------------------------------------------------------+
Later:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.05 Driver Version: 525.85.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:2D:00.0 Off | N/A |
| 30% 45C P8 6W / 200W | 1648MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Quadro RTX 4000 Off | 00000000:99:00.0 Off | N/A |
| 30% 42C P8 9W / 125W | 741MiB / 8192MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 338900 C chia_harvester 1646MiB |
| 1 N/A N/A 338900 C chia_harvester 738MiB |
+-----------------------------------------------------------------------------+
Exception fetching full proof ... recompute failed to produce a candidate
Today this ERROR was reported in debug.log:
ERROR Exception fetching full proof for ../plot-k33-c8-2023-02-27-04-04-xxxxxxxxxx.plot. recompute failed to produce a candidate
Besides this error everything runs fine.
What does that ERROR mean?
Can it happen sometimes or does this indicate some other problem ?
From debug.log
42048 2023-03-12T09:51:38.274 full_node chia.full_node.full_node: INFO Added unfinished_block xxx, not farmed by us, SP: 34 farmer response time: 4.0845, Pool pk xc
42048 xxx, validation time: 0.0291 seconds, pre_validation time 0.2545, cost: 2612975319, percent full: 23.754%
42049 2023-03-12T09:51:40.003 harvester chia.harvester.harvester: ERROR Exception fetching full proof for ../plot-k33-c8-2023-02-27-04-04-xxxxxxx.plot. re
42049 compute failed to produce a candidate
42050 2023-03-12T09:51:40.004 harvester chia.harvester.harvester: INFO 16 plots were eligible for farming ... Found 0 proofs. Time: 6.12164 s.
Every Single Compressed Plot Failed to Open
Hey, so I just recently tried out the new compressed plotting, and it doesn't seem to be going so well. I crafted around 497 plots in about 2 days with compression level 7. I craft all the plots on a physical HDD, mine are 20tb ones.
Afterwords I went and hooked up the enclosure to my farming system, and every single one of the 497 plots have failed to open.
The error displayed using the 'chia plots check' command is:
chia.plotting.manager : ERROR Failed to open file E:\plot-k32-c7-2023-02-26-16-58-16b39f2982ed05bed9e4d30f8c3fdcda32d69be8bdde28878f7325d307119d71.plot. Invalid plot file format Traceback (most recent call last):
File "chia\plotting\manager.py", line 274, in process_file
ValueError: Invalid plot file format
I tried restarting the enclosure, plugging the HDD with sata directly to my mobo, restarting the chia blockchain on my system, restarting the system, and renaming to *.temp then back to *.plot, none of these have worked.
I have done this method for all my other plots using the regular CPU plotting and it has always worked.
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