Cuda - Failad load CUDA Plugmins

[gikerus]

Hey i have that issue.
Bat file:
C:\xmrig\xmrig.exe --donate-level 1 --cuda --cuda-loader=C:\xmrig\xmrig-cuda.dll -o pool.minexmr.com:443 -u Pool --rig-id 515151 -k --tls --threads=2

CMD:

• ABOUT XMRig/5.10.0 MSVC/2019
• LIBS libuv/1.34.0 OpenSSL/1.1.1d hwloc/2.1.0
• HUGE PAGES permission granted
• 1GB PAGES unavailable
• CPU AMD Athlon(tm) II X2 250 Processor (1) x64 -AES
  L2:2.0 MB L3:0.0 MB 2C/2T NUMA:1
• MEMORY 1.9/7.7 GB (25%)
• DONATE 1%
• ASSEMBLY auto:none
• POOL Cleanup everything in GPU context when releasing it #1 pool.minexmr.com:443 algo auto
• COMMANDS hashrate, pause, resume
• OPENCL disabled
• CUDA disabled (failed to load CUDA plugin)

I have on this file:

Driver Nvidia: 390.77
Cuda installed: 9.0
Grafic cards: 2x nVIDIA GT 730

Do you need more information?
If not, can someone help me solve this problem?

[gikerus]

Someone can Help ?

[LesterCovax]

The highest supported CUDA version for GT 730 is v3.5. You're basically trying to use a steam engine to run a sports car.
https://developer.nvidia.com/cuda-gpus

[gikerus]

The highest supported CUDA version for GT 730 is v3.5. You're basically trying to use a steam engine to run a sports car.
https://developer.nvidia.com/cuda-gpus

coś chyba źle zobaczyłeś bo najwyższe sterowniki jakie mam to 388.13 a one wspieraja CUDA 9.0

po przeinstalowaniu komputera i instlacji wszytskiego na nowo pojawiło się cos nowego, tylko czy jest to do obejścia ? ponizej podsyłam błąd

` * ABOUT XMRig/5.11.3 MSVC/2019

• LIBS libuv/1.38.0 OpenSSL/1.1.1g hwloc/2.2.0
• HUGE PAGES permission granted
• 1GB PAGES unavailable
• CPU AMD Athlon(tm) II X2 250 Processor (1) x64 -AES
  L2:2.0 MB L3:0.0 MB 2C/2T NUMA:1
• MEMORY 1.8/7.7 GB (24%)
• DONATE 1%
• ASSEMBLY auto:none
• POOL Cleanup everything in GPU context when releasing it #1 pool.minexmr.com:443 algo auto
• COMMANDS hashrate, pause, resume
• OPENCL disabled
• CUDA 9.0/9.1/6.2.0
• NVML 9.388.13/388.13 press e for health report
• CUDA GPU #0 02:00.0 GeForce GT 730 901/2505 MHz smx:2 arch:35 mem:1698/2048 MB
• CUDA GPU Cleanup everything in GPU context when releasing it #1 03:00.0 GeForce GT 730 1400/800 MHz smx:2 arch:21 mem:1689/2048 MB
  [2020-06-12 22:08:37.583] net use pool pool.minexmr.com:443 TLSv1.3 94.130.164.163
  [2020-06-12 22:08:37.584] net fingerprint (SHA-256): "f8cb85d6dc856748d376b48e6b87f90900b3f683fe505ef59de570296761d14b"
  [2020-06-12 22:08:37.585] net new job from pool.minexmr.com:443 diff 175004 algo rx/0 height 2119215
  [2020-06-12 22:08:37.585] cpu use argon2 implementation SSE2
  [2020-06-12 22:08:37.586] rx init dataset algo rx/0 (2 threads) seed d10ce0939583c30c...
  [2020-06-12 22:08:37.603] rx allocated 2336 MB (2080+256) huge pages 100% 1168/1168 +JIT (17 ms)
  [2020-06-12 22:09:01.652] rx dataset ready (24048 ms)
  [2020-06-12 22:09:01.656] cpu use profile rx (2 threads) scratchpad 2048 KB
  [2020-06-12 22:09:01.695] cpu READY threads 2/2 (2) huge pages 100% 2/2 memory 4096 KB (36 ms)
  [2020-06-12 22:09:01.726] nv use profile rx (2 threads) scratchpad 2048 KB
  | # | GPU | BUS ID | I | T | B | BF | BS | MEM | NAME
  | 0 | 0 | 02:00.0 | 128 | 32 | 4 | 1 | 25 | 256 | GeForce GT 730
  | 1 | 1 | 03:00.0 | 128 | 32 | 4 | 1 | 25 | 256 | GeForce GT 730
  [2020-06-12 22:09:16.262] nv READY threads 2/2 (14394 ms)
  [2020-06-12 22:09:16.338] nv thread Cleanup everything in GPU context when releasing it #1 failed with error DatasetHost::reg:50 "out of memory"
  [2020-06-12 22:09:16.397] nv thread #0 failed with error <randomx_prepare>:36 "invalid argument"
  [2020-06-12 22:09:35.063] net new job from pool.minexmr.com:443 diff 175004 algo rx/0 height 2119215
  [2020-06-12 22:09:40.444] net new job from pool.minexmr.com:443 diff 175004 algo rx/0 height 2119216
  [2020-06-12 22:10:05.979] nv #0 02:00.0 0W 36C fan0:39%
  [2020-06-12 22:10:06.029] nv Cleanup everything in GPU context when releasing it #1 03:00.0 0W 36C fan0:35%`

[gikerus]

chodzi o te dwa błędy jest to do obejścia czy nie ?

[gikerus]

podsyłam kod jonson

{
"api": {
"id": null,
"worker-id": null
},
"http": {
"enabled": false,
"host": "127.0.0.1",
"port": 0,
"access-token": null,
"restricted": true
},
"autosave": true,
"background": false,
"colors": true,
"randomx": {
"init": -1,
"mode": "auto",
"1gb-pages": false,
"rdmsr": true,
"wrmsr": true,
"numa": true
},
"cpu": {
"enabled": true,
"huge-pages": true,
"hw-aes": null,
"priority": null,
"memory-pool": false,
"yield": true,
"asm": true,
"argon2-impl": null,
"astrobwt-max-size": 550,
"astrobwt-avx2": false,
"argon2": [0, 1],
"astrobwt": [0, 1],
"cn": [
[1, 0],
[1, 1]
],
"cn-heavy": [
[1, -1]
],
"cn-lite": [
[1, 0],
[1, 1]
],
"cn-pico": [
[2, 0],
[2, 1]
],
"rx": [0, 1],
"rx/wow": [0, 1],
"cn/0": false,
"cn-lite/0": false,
"rx/arq": "rx/wow",
"rx/keva": "rx/wow"
},
"opencl": {
"enabled": false,
"cache": true,
"loader": null,
"platform": "AMD",
"adl": true
},
"cuda": {
"enabled": true,
"loader": null,
"nvml": true,
"astrobwt": [
{
"index": 0,
"threads": 32,
"blocks": 5,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 32,
"blocks": 5,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"cn": [
{
"index": 0,
"threads": 128,
"blocks": 6,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 64,
"blocks": 4,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"cn-heavy": [
{
"index": 0,
"threads": 64,
"blocks": 6,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 40,
"blocks": 4,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"cn-lite": [
{
"index": 0,
"threads": 128,
"blocks": 6,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 64,
"blocks": 4,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"cn-pico": [
{
"index": 0,
"threads": 4,
"blocks": 16,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 4,
"blocks": 16,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"cn/2": [
{
"index": 0,
"threads": 4,
"blocks": 16,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
},
{
"index": 1,
"threads": 4,
"blocks": 16,
"bfactor": 1,
"bsleep": 25,
"affinity": -1
}
],
"rx": [
{
"index": 0,
"threads": 32,
"blocks": 4,
"bfactor": 1,
"bsleep": 25,
"affinity": -1,
"dataset_host": true
},
{
"index": 1,
"threads": 32,
"blocks": 4,
"bfactor": 1,
"bsleep": 25,
"affinity": -1,
"dataset_host": true
}
],
"cn/0": false,
"cn-lite/0": false
},
"donate-level": 1,
"donate-over-proxy": 1,
"log-file": null,
"pools": [
{
"algo": null,
"coin": null,
"url": "pool.minexmr.com:443",
"user":
"pass":
"rig-id": "51",
"nicehash": false,
"keepalive": true,
"enabled": true,
"tls": true,
"tls-fingerprint": null,
"daemon": false,
"socks5": null,
"self-select": null
}
],
"print-time": 60,
"health-print-time": 60,
"retries": 5,
"retry-pause": 5,
"syslog": false,
"tls": {
"enabled": false,
"protocols": null,
"cert": null,
"cert_key": null,
"ciphers": null,
"ciphersuites": null,
"dhparam": null
},
"user-agent": null,
"verbose": 0,
"watch": true
}

[Spudz76]

Not enough memory for RandomX on both system RAM (1.8GB free) and GPU memory (256M total each) Requires 2.25GB.

Second problem is arch 2x cards maximum CUDA Toolkit 8.0 so then the first card arch 3x is only that will work with CUDA 9.x. With plugin on CUDA8.0 it should still work with 9.1 driver level you already have. RandomX will not perform even if it did have enough memory.

[LesterCovax]

I meant to follow up after originally posting, but I may have mistaken CUDA compute version with CUDA version (which are quite different)...so you can prob ignore my comment.

…

On Sun, Jun 14, 2020, 1:27 PM Tony Butler ***@***.***> wrote: Not enough memory for RandomX on both system RAM (1.8GB free) and GPU memory (256M total each) Requires 2.25GB. Second problem is arch 2x cards maximum CUDA Toolkit 8.0 so then the first card arch 3x is only that will work with CUDA 9.x. With plugin on CUDA8.0 it should still work with 9.1 driver level you already have. RandomX will not perform even if it did have enough memory. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#43 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AIJ4OMSPROPJKSTLYJQKJM3RWUCBTANCNFSM4MNWI7SQ> .