Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

"Cannot find any NVIDIA platform" error #25

Open
uniquelemon opened this issue Apr 28, 2024 · 2 comments
Open

"Cannot find any NVIDIA platform" error #25

uniquelemon opened this issue Apr 28, 2024 · 2 comments

Comments

@uniquelemon
Copy link

uniquelemon commented Apr 28, 2024 •
edited
Loading

Hi, I am running AutoDock on WSL2 with CUDA version 12.4, and I have tried Boost versions 1.77, 1.83 and 1.85.
However, I encounter the error 'Cannot find any NVIDIA platform' during tests.
Since my WSL2 environment can normally run AlphaFold2, and both nvidia-smi and clinfo commands output information correctly,

$  ./AutoDock-Vina-GPU-2-1 --config ./input_file_example/2bm2_config.txt
#################################################################
# If you used AutoDockVina-GPU 2.1 in your work, please cite:   #
#                                                               #
# Ding, Ji, et al. Vina-GPU 2.0: Further Accelerating AutoDock  #
# Vina and Its Derivatives with Graphics Processing Units.      #
# Journal of Chemical Information and Modeling (2023).          #
#                                                               #
# DOI https://doi.org/10.1021/acs.jcim.2c01504                  #
#                                                               #
# Shidi, Tang, Chen Ruiqi, Lin Mengru, Lin Qingde,              #
# Zhu Yanxiang, Wu Jiansheng, Hu Haifeng, and Ling Ming.        #
# Accelerating AutoDock Vina with GPUs.                         #
# Molecules 27.9 (2022): 3041.                                  #
#                                                               #
# DOI https://doi.org/10.3390/molecules27093041                 #
#                                                               #
# And also the origin AutoDock Vina paper:                      #
# O. Trott, A. J. Olson,                                        #
# AutoDock Vina: improving the speed and accuracy of docking    #
# with a new scoring function, efficient optimization and       #
# multithreading, Journal of Computational Chemistry 31 (2010)  #
# 455-461                                                       #
#                                                               #
# DOI 10.1002/jcc.21334                                         #
#                                                               #
#################################################################

Using virtual sreening mode

Output will be in the directory ./test_out
Reading input ... done.
Setting up the scoring function ... done.
Using heuristic search_depth
Analyzing the binding site ... done.
Cannot find any NVIDIA platform

$ clinfo
Number of platforms 1
Platform Name Portable Computing Language
Platform Vendor The pocl project
Platform Version OpenCL 3.0 PoCL 5.0 Linux, RelWithDebInfo, RELOC, SPIR, LLVM 14.0.0, SLEEF, CUDA, POCL_DEBUG
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_icd cl_pocl_content_size
Platform Extensions with Version cl_khr_icd 0x400000 (1.0.0)
cl_pocl_content_size 0x400000 (1.0.0)
Platform Numeric Version 0xc00000 (3.0.0)
Platform Extensions function suffix POCL
Platform Host timer resolution 0ns

Platform Name Portable Computing Language
Number of devices 1
Device Name NVIDIA GeForce RTX 3090
Device Vendor NVIDIA Corporation
Device Vendor ID 0x10de
Device Version OpenCL 3.0 PoCL HSTR: CUDA-sm_86
Device Numeric Version 0xc00000 (3.0.0)
Driver Version 5.0
Device OpenCL C Version OpenCL C 1.2 PoCL
Device OpenCL C all versions OpenCL C 0x400000 (1.0.0)
OpenCL C 0x401000 (1.1.0)
OpenCL C 0x402000 (1.2.0)
OpenCL C 0xc00000 (3.0.0)
Device OpenCL C features __opencl_c_images 0xc00000 (3.0.0)
__opencl_c_atomic_order_acq_rel 0xc00000 (3.0.0)
__opencl_c_atomic_order_seq_cst 0xc00000 (3.0.0)
__opencl_c_atomic_scope_device 0xc00000 (3.0.0)
__opencl_c_program_scope_global_variables 0xc00000 (3.0.0)
__opencl_c_generic_address_space 0xc00000 (3.0.0)
__opencl_c_fp16 0xc00000 (3.0.0)
__opencl_c_fp64 0xc00000 (3.0.0)
Latest comfornace test passed (n/a)
Device Type GPU
Device Topology (NV) PCI-E, 0000:08:00.0
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 82
Max clock frequency 1860MHz
Compute Capability (NV) 8.6
Device Partition (core)
Max number of sub-devices 1
Supported partition types None
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 1024x1024x64
Max work group size 1024
Preferred work group size multiple (device) 32
Preferred work group size multiple (kernel) 32
Warp size (NV) 32
Max sub-groups per work group 32
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (cl_khr_fp16)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (cl_khr_fp16)
Denormals No
Infinity and NANs No
Round to nearest No
Round to zero No
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Single-precision Floating-point support (core)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Correctly-rounded divide and sqrt operations No
Double-precision Floating-point support (cl_khr_fp64)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Address bits 64, Little-Endian
Global memory size 25769148416 (24GiB)
Error Correction support No
Max memory allocation 6442287104 (6GiB)
Unified memory for Host and Device No
Integrated memory (NV) No
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing Yes
Fine-grained buffer sharing Yes
Fine-grained system sharing No
Atomics No
Minimum alignment for any data type 128 bytes
Alignment of base address 4096 bits (512 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 64 bytes
Atomic memory capabilities relaxed, work-group scope
Atomic fence capabilities relaxed, acquire/release, work-group scope
Max size for global variable 0
Preferred total size of global vars 0
Global Memory cache type None
Image support No
Pipe support No
Max number of pipe args 0
Max active pipe reservations 0
Max pipe packet size 0
Local memory type Local
Local memory size 49152 (48KiB)
Registers per block (NV) 65536
Max number of constant args 8
Max constant buffer size 65536 (64KiB)
Generic address space support Yes
Max size of kernel argument 4352 (4.25KiB)
Queue properties (on host)
Out-of-order execution No
Profiling Yes
Device enqueue capabilities (n/a)
Queue properties (on device)
Out-of-order execution No
Profiling No
Preferred size 0
Max size 0
Max queues on device 0
Max events on device 0
Prefer user sync for interop Yes
Profiling timer resolution 1ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Non-uniform work-groups No
Work-group collective functions No
Sub-group independent forward progress Yes
Kernel execution timeout (NV) Yes
Concurrent copy and kernel execution (NV) Yes
Number of async copy engines 1
IL version (n/a)
ILs with version (n/a)
SPIR versions (n/a)
printf() buffer size 16777216 (16MiB)
Built-in kernels pocl.mul.i32;pocl.add.i32;pocl.dnn.conv2d_int8_relu;pocl.sgemm.local.f32;pocl.sgemm.tensor.f16f16f32;pocl.sgemm_ab.tensor.f16f16f32;pocl.abs.f32;pocl.add.i8;org.khronos.openvx.scale_image.nn.u8;org.khronos.openvx.scale_image.bl.u8;org.khronos.openvx.tensor_convert_depth.wrap.u8.f32
Built-in kernels with version pocl.mul.i32 0x402000 (1.2.0)
pocl.add.i32 0x402000 (1.2.0)
pocl.dnn.conv2d_int8_relu 0x402000 (1.2.0)
pocl.sgemm.local.f32 0x402000 (1.2.0)
pocl.sgemm.tensor.f16f16f32 0x402000 (1.2.0)
pocl.sgemm_ab.tensor.f16f16f32 0x402000 (1.2.0)
pocl.abs.f32 0x402000 (1.2.0)
pocl.add.i8 0x402000 (1.2.0)
org.khronos.openvx.scale_image.nn.u8 0x402000 (1.2.0)
org.khronos.openvx.scale_image.bl.u8 0x402000 (1.2.0)
org.khronos.openvx.tensor_convert_depth.wrap.u8.f32 0x402000 (1.2.0)
Device Extensions cl_khr_byte_addressable_store cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_nv_device_attribute_query cl_khr_spir cl_khr_fp16 cl_khr_fp64
Device Extensions with Version cl_khr_byte_addressable_store 0x400000 (1.0.0)
cl_khr_global_int32_base_atomics 0x400000 (1.0.0)
cl_khr_global_int32_extended_atomics 0x400000 (1.0.0)
cl_khr_local_int32_base_atomics 0x400000 (1.0.0)
cl_khr_local_int32_extended_atomics 0x400000 (1.0.0)
cl_khr_int64_base_atomics 0x400000 (1.0.0)
cl_khr_int64_extended_atomics 0x400000 (1.0.0)
cl_nv_device_attribute_query 0x400000 (1.0.0)
cl_khr_spir 0x801000 (2.1.0)
cl_khr_fp16 0x400000 (1.0.0)
cl_khr_fp64 0x400000 (1.0.0)

NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform
clCreateContext(NULL, ...) [default] No platform
clCreateContext(NULL, ...) [other] Success [POCL]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090
(base) zouyu@B550 ~/07.Software/AutoDock/Vina-GPU-2.1-main/AutoDock-Vina-GPU-2.1
$ clinfo
Number of platforms 1
Platform Name Portable Computing Language
Platform Vendor The pocl project
Platform Version OpenCL 3.0 PoCL 5.0 Linux, RelWithDebInfo, RELOC, SPIR, LLVM 14.0.0, SLEEF, CUDA, POCL_DEBUG
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_icd cl_pocl_content_size
Platform Extensions with Version cl_khr_icd 0x400000 (1.0.0)
cl_pocl_content_size 0x400000 (1.0.0)
Platform Numeric Version 0xc00000 (3.0.0)
Platform Extensions function suffix POCL
Platform Host timer resolution 0ns

Platform Name Portable Computing Language
Number of devices 1
Device Name NVIDIA GeForce RTX 3090
Device Vendor NVIDIA Corporation
Device Vendor ID 0x10de
Device Version OpenCL 3.0 PoCL HSTR: CUDA-sm_86
Device Numeric Version 0xc00000 (3.0.0)
Driver Version 5.0
Device OpenCL C Version OpenCL C 1.2 PoCL
Device OpenCL C all versions OpenCL C 0x400000 (1.0.0)
OpenCL C 0x401000 (1.1.0)
OpenCL C 0x402000 (1.2.0)
OpenCL C 0xc00000 (3.0.0)
Device OpenCL C features __opencl_c_images 0xc00000 (3.0.0)
__opencl_c_atomic_order_acq_rel 0xc00000 (3.0.0)
__opencl_c_atomic_order_seq_cst 0xc00000 (3.0.0)
__opencl_c_atomic_scope_device 0xc00000 (3.0.0)
__opencl_c_program_scope_global_variables 0xc00000 (3.0.0)
__opencl_c_generic_address_space 0xc00000 (3.0.0)
__opencl_c_fp16 0xc00000 (3.0.0)
__opencl_c_fp64 0xc00000 (3.0.0)
Latest comfornace test passed (n/a)
Device Type GPU
Device Topology (NV) PCI-E, 0000:08:00.0
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 82
Max clock frequency 1860MHz
Compute Capability (NV) 8.6
Device Partition (core)
Max number of sub-devices 1
Supported partition types None
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 1024x1024x64
Max work group size 1024
Preferred work group size multiple (device) 32
Preferred work group size multiple (kernel) 32
Warp size (NV) 32
Max sub-groups per work group 32
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (cl_khr_fp16)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (cl_khr_fp16)
Denormals No
Infinity and NANs No
Round to nearest No
Round to zero No
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Single-precision Floating-point support (core)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Correctly-rounded divide and sqrt operations No
Double-precision Floating-point support (cl_khr_fp64)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Address bits 64, Little-Endian
Global memory size 25769148416 (24GiB)
Error Correction support No
Max memory allocation 6442287104 (6GiB)
Unified memory for Host and Device No
Integrated memory (NV) No
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing Yes
Fine-grained buffer sharing Yes
Fine-grained system sharing No
Atomics No
Minimum alignment for any data type 128 bytes
Alignment of base address 4096 bits (512 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 64 bytes
Atomic memory capabilities relaxed, work-group scope
Atomic fence capabilities relaxed, acquire/release, work-group scope
Max size for global variable 0
Preferred total size of global vars 0
Global Memory cache type None
Image support No
Pipe support No
Max number of pipe args 0
Max active pipe reservations 0
Max pipe packet size 0
Local memory type Local
Local memory size 49152 (48KiB)
Registers per block (NV) 65536
Max number of constant args 8
Max constant buffer size 65536 (64KiB)
Generic address space support Yes
Max size of kernel argument 4352 (4.25KiB)
Queue properties (on host)
Out-of-order execution No
Profiling Yes
Device enqueue capabilities (n/a)
Queue properties (on device)
Out-of-order execution No
Profiling No
Preferred size 0
Max size 0
Max queues on device 0
Max events on device 0
Prefer user sync for interop Yes
Profiling timer resolution 1ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Non-uniform work-groups No
Work-group collective functions No
Sub-group independent forward progress Yes
Kernel execution timeout (NV) Yes
Concurrent copy and kernel execution (NV) Yes
Number of async copy engines 1
IL version (n/a)
ILs with version (n/a)
SPIR versions (n/a)
printf() buffer size 16777216 (16MiB)
Built-in kernels pocl.mul.i32;pocl.add.i32;pocl.dnn.conv2d_int8_relu;pocl.sgemm.local.f32;pocl.sgemm.tensor.f16f16f32;pocl.sgemm_ab.tensor.f16f16f32;pocl.abs.f32;pocl.add.i8;org.khronos.openvx.scale_image.nn.u8;org.khronos.openvx.scale_image.bl.u8;org.khronos.openvx.tensor_convert_depth.wrap.u8.f32
Built-in kernels with version pocl.mul.i32 0x402000 (1.2.0)
pocl.add.i32 0x402000 (1.2.0)
pocl.dnn.conv2d_int8_relu 0x402000 (1.2.0)
pocl.sgemm.local.f32 0x402000 (1.2.0)
pocl.sgemm.tensor.f16f16f32 0x402000 (1.2.0)
pocl.sgemm_ab.tensor.f16f16f32 0x402000 (1.2.0)
pocl.abs.f32 0x402000 (1.2.0)
pocl.add.i8 0x402000 (1.2.0)
org.khronos.openvx.scale_image.nn.u8 0x402000 (1.2.0)
org.khronos.openvx.scale_image.bl.u8 0x402000 (1.2.0)
org.khronos.openvx.tensor_convert_depth.wrap.u8.f32 0x402000 (1.2.0)
Device Extensions cl_khr_byte_addressable_store cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_nv_device_attribute_query cl_khr_spir cl_khr_fp16 cl_khr_fp64
Device Extensions with Version cl_khr_byte_addressable_store 0x400000 (1.0.0)
cl_khr_global_int32_base_atomics 0x400000 (1.0.0)
cl_khr_global_int32_extended_atomics 0x400000 (1.0.0)
cl_khr_local_int32_base_atomics 0x400000 (1.0.0)
cl_khr_local_int32_extended_atomics 0x400000 (1.0.0)
cl_khr_int64_base_atomics 0x400000 (1.0.0)
cl_khr_int64_extended_atomics 0x400000 (1.0.0)
cl_nv_device_attribute_query 0x400000 (1.0.0)
cl_khr_spir 0x801000 (2.1.0)
cl_khr_fp16 0x400000 (1.0.0)
cl_khr_fp64 0x400000 (1.0.0)

NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform
clCreateContext(NULL, ...) [default] No platform
clCreateContext(NULL, ...) [other] Success [POCL]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) Success (1)
Platform Name Portable Computing Language
Device Name NVIDIA GeForce RTX 3090

$  nvidia-smi
Sun Apr 28 20:36:38 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.76.01              Driver Version: 552.22         CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| 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 3090        On  |   00000000:08:00.0  On |                  N/A |
| 51%   55C    P0            122W /  370W |    1665MiB /  24576MiB |     25%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

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

I am quite puzzled.
Have any suggestions? Thank you,

Lee
@zhangj5
Copy link

zhangj5 commented Dec 12, 2024

Dear Lee,

I encountered the same situation as you described. Have you found a solution to this problem?

Jinsong

@uniquelemon
Copy link
Author

Dear Lee,

I encountered the same situation as you described. Have you found a solution to this problem?

Jinsong

Dear Jinsong,

The problem I encountered was not resolved after trying many methods, so I finally chose to use AutoDock-GPU for docking.

Lee

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@zhangj5 @uniquelemon