GPUEngine: Kernel: no kernel image is available for execution on the device / App [vanitysearch] exited with [0] code.

[jig0901]

Good evening,

I have been able to run your Cuda-128 docker image with my RTX 4070 just fine. However, today I installed a new RTX 5070 Ti and started receiving the above error message. At the moment I have both GPUs installed and the 4070 is running fine but the 5070 Ti exits out with the error. Please see my "settings.txt" file below.

target_puzzle=68
app_type=vanitysearch
app_path=vanitysearch
app_arguments=
user_token=
worker_name=
gpu_count=2
gpu_index=0
gpu_seperated_range=true
scan_rewards=true
custom_range=none
api_share=none
telegram_share=true
telegram_accesstoken=
telegram_chatid=
telegram_share_eachkey=false
untrusted_computer=false
test_mode=false
force_continue=false

[ilkerccom]

Hello, use the docker image named cuda-128 for the 5000 series. The built vanitysearch that comes with the application supports up to the 4000 series.

[jig0901]

Hello,

Yes, I am using the cuda-128 docker image. I am getting the above error with cuda-128 image.

[jig0901]

@ilkerccom I built BitcrackRandomiser locally and running that executable with the same settings seems to work. I initially installed Cuda v12.8.1 and later installed Cuda v12.6.

nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Fri_Jun_14_16:44:19_Pacific_Daylight_Time_2024
Cuda compilation tools, release 12.6, V12.6.20
Build cuda_12.6.r12.6/compiler.34431801_0

[eliaspoliceno]

I'm experiencing the same issue here.
I have created my settings.txt file:

target_puzzle=71
app_type=vanitysearch
app_path=vanitysearch
app_arguments=
user_token=
worker_name=server-4
scan_rewards=true
gpu_count=1
gpu_index=0
api_share=none
telegram_share=true
telegram_accesstoken=
telegram_chatid=
telegram_share_eachkey=false
untrusted_computer=false
test_mode=false
force_continue=true

Then I executed:
docker run --gpus all -it -v .:/tmp/host ilkercndk/bitcrackrandomiser:cuda-128

Copied the settings.txt from my machine to the docker container.
Then I started the app:
dotnet BitcrackRandomiser.dll

The output is:

CUDA Version 12.8.0

Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.

PID= 28
[2025-07-08-22:31:21] [Info] Press to edit settings or wait for 3 seconds to load app with <settings.txt>
[2025-07-08-22:31:21] [Info] Please wait while app is starting...
[2025-07-08-22:31:21] [Info] [v1.4.1.0] [vanitysearch] starting... Puzzle: [71]
[2025-07-08-22:31:21] [Info] Target address: 1PWo3JeB9jrGwfHDNpdGK54CRas7fsVzXU
[2025-07-08-22:31:21] [Info] Test mode is passive.
[2025-07-08-22:31:21] [Info] Custom range: [none]
[2025-07-08-22:31:21] [Info] API share: False / Telegram share: True
[2025-07-08-22:31:21] [Info] Untrusted computer: False
[2025-07-08-22:31:21] [Info] Progress: Visit the [btcpuzzle.info] for statistics.
[2025-07-08-22:31:21] [Info] Worker name: server-4

[keyspace] start= 5B803A800000000000 [HEX=5B803A8] [keyspace] end= 5B803A9FFFFFFFFFFF [HEX=5B803A8] Search: 7 addresses (Lookup size 7,[1,1]) [Compressed] [HEX=5B803A8] Current task START time: Tue Jul 8 22:31:21 2025 [HEX=5B803A8] VanitySearch v1.16 Linux with BitCrack integration [HEX=5B803A8] Number of CPU thread: 0 [HEX=5B803A8] GPUEngine: Kernel: no kernel image is available for execution on the device [HEX=5B803A8] Current task END time: Tue Jul 8 22:31:24 2025 [HEX=5B803A8] [2025-07-08-22:31:28] [Info] App [vanitysearch] exited with [0] code.

I tried several different driver versions, but nothing worked. It appears to be something with the CUDA or vanitysearch app. This are the versions that I have downloaded:
ls -lah NVIDIA-Linux-x86_64-57*
-rwxr-xr-x 1 root root 359M Feb 25 16:14 NVIDIA-Linux-x86_64-570.124.04.run
-rwxr-xr-x 1 root root 359M Jun 13 18:40 NVIDIA-Linux-x86_64-570.169.run
-rwxr-xr-x 1 root root 370M Jun 30 14:47 NVIDIA-Linux-x86_64-575.64.03.run
-rwxr-xr-x 1 root root 370M Jun 12 10:21 NVIDIA-Linux-x86_64-575.64.run

Some more information:
nvidia-smi
Tue Jul 8 19:36:50 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.06 Driver Version: 570.124.06 CUDA Version: 12.8 |
|-----------------------------------------+------------------------+----------------------+
| 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 RTX 5090 Off | 00000000:01:00.0 Off | N/A |
| 0% 48C P8 31W / 575W | 1MiB / 32607MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+

The OS is Debian 12 bookworm.

docker -v
Docker version 28.1.1, build 4eba377

uname -a
Linux server-4 6.1.0-37-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.140-1 (2025-05-22) x86_64 GNU/Linux

The CPU is an AMD Ryzen 7 7700X 8-Core Processor.

What are the steps to compile and run it locally, or is there any other version that I can try to run to see if it works?

[eliaspoliceno]

Changing this project's Dockerfile to recompile Vanity-Search-V2 made it work:

FROM ilkercndk/bitcrackrandomiser:cuda-128
RUN apt update && apt install libc6-dev -y
COPY settings.txt /app/bitcrackrandomiser/
COPY run.sh /app/bitcrackrandomiser/
WORKDIR /
RUN git clone https://github.com/ilkerccom/VanitySearch-V2.git
WORKDIR /VanitySearch-V2
RUN sed -i 's|/usr/local/cuda-12.2|/usr/local/cuda-12.8|g' Makefile
RUN sed -i 's|ccap=89|ccap=120|g' Makefile
RUN make gpu=1 all && cp -f vanitysearch /app/bitcrackrandomiser/Apps/vanitysearch/vanitysearch
WORKDIR /app/bitcrackrandomiser
CMD ["./run.sh"]