'Err-4:CL_MEM_OBJECT_ALLOCATION_FAILURE' When test D-LARGE format with AutoDock-Vina-GPU-2.1

[marramWang]

Thanks for your great efforts on enlarging the atom num and size of grid boxes. However I encountered errors

' Err-4:CL_MEM_OBJECT_ALLOCATION_FAILURE'

when using AutoDock-GPU-Vina-2.1 run the test data in format of D-LARGE format (MAKEFILE).The same test data works well in the D-SMALL format. this.

Full Running page:

{CITE Infomation}
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.
GPU Platform: NVIDIA CUDA
GPU Device: NVIDIA GeForce RTX 3080
Using random seed: -1345958431
Err-4:CL_MEM_OBJECT_ALLOCATION_FAILURE

#my revised part in Makefile Listed below:

WORK_DIR=/home/wr/softwares/Vina-GPU-2.1-main/AutoDock-Vina-GPU-2.1
BOOST_LIB_PATH=/home/wr/softwares/boost_1_77_0
OPENCL_LIB_PATH=/usr/local/cuda
OPENCL_VERSION=-DOPENCL_3_0
GPU_PLATFORM=-DNVIDIA_PLATFORM
DOCKING_BOX_SIZE=-DLARGE_BOX

I unlimited the Stack size as 'unlimited', actually, 8192,81920 and 100000 have been tried as well but still,the same error before.
ulimit -a

core file size (blocks, -c) unlimited
data seg size (kbytes, -d) unlimited
scheduling priority (-e) 0
file size (blocks, -f) unlimited
pending signals (-i) 1029981
max locked memory (kbytes, -l) 32968648
max memory size (kbytes, -m) unlimited
open files (-n) 1024
pipe size (512 bytes, -p) 8
POSIX message queues (bytes, -q) 819200
real-time priority (-r) 0
stack size (kbytes, -s) unlimited
cpu time (seconds, -t) unlimited
max user processes (-u) 1029981
virtual memory (kbytes, -v) unlimited
file locks (-x) unlimited

clinfo

`Number of platforms 1
Platform Name NVIDIA CUDA
Platform Vendor NVIDIA Corporation
Platform Version OpenCL 3.0 CUDA 12.2.79
Platform Profile FULL_PROFILE
Platform Extensions 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_fp64 cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_device_uuid cl_khr_pci_bus_info cl_khr_external_semaphore cl_khr_external_memory cl_khr_external_semaphore_opaque_fd cl_khr_external_memory_opaque_fd
Platform Extensions with Version 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_fp64 0x400000 (1.0.0)
cl_khr_3d_image_writes 0x400000 (1.0.0)
cl_khr_byte_addressable_store 0x400000 (1.0.0)
cl_khr_icd 0x400000 (1.0.0)
cl_khr_gl_sharing 0x400000 (1.0.0)
cl_nv_compiler_options 0x400000 (1.0.0)
cl_nv_device_attribute_query 0x400000 (1.0.0)
cl_nv_pragma_unroll 0x400000 (1.0.0)
cl_nv_copy_opts 0x400000 (1.0.0)
cl_nv_create_buffer 0x400000 (1.0.0)
cl_khr_int64_base_atomics 0x400000 (1.0.0)
cl_khr_int64_extended_atomics 0x400000 (1.0.0)
cl_khr_device_uuid 0x400000 (1.0.0)
cl_khr_pci_bus_info 0x400000 (1.0.0)
cl_khr_external_semaphore 0x9000 (0.9.0)
cl_khr_external_memory 0x9000 (0.9.0)
cl_khr_external_semaphore_opaque_fd 0x9000 (0.9.0)
cl_khr_external_memory_opaque_fd 0x9000 (0.9.0)
Platform Numeric Version 0xc00000 (3.0.0)
Platform Extensions function suffix NV
Platform Host timer resolution 0ns

Platform Name NVIDIA CUDA
Number of devices 1
Device Name NVIDIA GeForce RTX 3080
Device Vendor NVIDIA Corporation
Device Vendor ID 0x10de
Device Version OpenCL 3.0 CUDA
Device UUID fa4cf603-d831-d614-c6b1-8ad9933a48e5
Driver UUID fa4cf603-d831-d614-c6b1-8ad9933a48e5
Valid Device LUID No
Device LUID 6d69-637300000000
Device Node Mask 0
Device Numeric Version 0xc00000 (3.0.0)
Driver Version 535.54.03
Device OpenCL C Version OpenCL C 1.2
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_fp64 0xc00000 (3.0.0)
__opencl_c_images 0xc00000 (3.0.0)
__opencl_c_int64 0xc00000 (3.0.0)
__opencl_c_3d_image_writes 0xc00000 (3.0.0)
Latest comfornace test passed v2022-10-05-00
Device Type GPU
Device Topology (NV) PCI-E, 0000:73:00.0
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 68
Max clock frequency 1710MHz
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 0
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (n/a)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (n/a)
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 Yes
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 10487529472 (9.767GiB)
Error Correction support No
Max memory allocation 2621882368 (2.442GiB)
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 No
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 0 bytes
Global 0 bytes
Local 0 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 Read/Write
Global Memory cache size 1949696 (1.859MiB)
Global Memory cache line size 128 bytes
Image support Yes
Max number of samplers per kernel 32
Max size for 1D images from buffer 268435456 pixels
Max 1D or 2D image array size 2048 images
Max 2D image size 32768x32768 pixels
Max 3D image size 16384x16384x16384 pixels
Max number of read image args 256
Max number of write image args 32
Max number of read/write image args 0
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 9
Max constant buffer size 65536 (64KiB)
Generic address space support No
Max size of kernel argument 32764 (32KiB)
Queue properties (on host)
Out-of-order execution Yes
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 No
Profiling timer resolution 1000ns
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 No
Kernel execution timeout (NV) No
Concurrent copy and kernel execution (NV) Yes
Number of async copy engines 2
IL version (n/a)
ILs with version <printDeviceInfo:186: get CL_DEVICE_ILS_WITH_VERSION : error -30>
printf() buffer size 1048576 (1024KiB)
Built-in kernels (n/a)
Built-in kernels with version <printDeviceInfo:190: get CL_DEVICE_BUILT_IN_KERNELS_WITH_VERSION : error -30>
Device Extensions 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_fp64 cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_copy_opts cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_device_uuid cl_khr_pci_bus_info cl_khr_external_semaphore cl_khr_external_memory cl_khr_external_semaphore_opaque_fd cl_khr_external_memory_opaque_fd
Device Extensions with Version 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_fp64 0x400000 (1.0.0)
cl_khr_3d_image_writes 0x400000 (1.0.0)
cl_khr_byte_addressable_store 0x400000 (1.0.0)
cl_khr_icd 0x400000 (1.0.0)
cl_khr_gl_sharing 0x400000 (1.0.0)
cl_nv_compiler_options 0x400000 (1.0.0)
cl_nv_device_attribute_query 0x400000 (1.0.0)
cl_nv_pragma_unroll 0x400000 (1.0.0)
cl_nv_copy_opts 0x400000 (1.0.0)
cl_nv_create_buffer 0x400000 (1.0.0)
cl_khr_int64_base_atomics 0x400000 (1.0.0)
cl_khr_int64_extended_atomics 0x400000 (1.0.0)
cl_khr_device_uuid 0x400000 (1.0.0)
cl_khr_pci_bus_info 0x400000 (1.0.0)
cl_khr_external_semaphore 0x9000 (0.9.0)
cl_khr_external_memory 0x9000 (0.9.0)
cl_khr_external_semaphore_opaque_fd 0x9000 (0.9.0)
cl_khr_external_memory_opaque_fd 0x9000 (0.9.0)

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 [NV]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) Invalid device type for platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform

I have been struggled with this for quite a time, it will be great helpful if anyone figures out what is going on here?

[Glinttsd]

Hi, can you offer the memory capacity of the GPU? Larger box requires larger memory, which maybe your problem.

[marramWang]

Hi, can you offer the memory capacity of the GPU? Larger box requires larger memory, which maybe your problem.

nvidia-smi

Tue Jun 11 10:25:47 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.54.03 Driver Version: 535.54.03 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| 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 3080 Off | 00000000:73:00.0 On | N/A |
| 0% 55C P8 17W / 320W | 2MiB / 10240MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+

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

[marramWang]

Hi, can you offer the memory capacity of the GPU? Larger box requires larger memory, which maybe your problem.

Hi again, thanks for your kind response before. thanks to your helpful reminder, i checked the GPU capacity again:
nvidia-smi shows 'Memory-Usage' stay 2MiB/10240MiB,
and according to clinfo, my 'Global memory size' is 10487529472 (9.767GiB) and 'Max memory allocation' is 2621882368 (2.442GiB), (other information listed on the primary issue #34 (comment))

is that enough for large boxes? how much memory required under D-LARGE format? Or it would be helpful if it is convenient for you to tell me which script i should check to find the required GPU capacity for larger boxes?

Since I have changed the stack size into 'unlimited', with ulimit -s unlimited ,which still cannot solve the problem.

Sincerely waiting for your replying, Thanks a lot.

[Glinttsd]

Hi, the large box is tested in the enviroment of V100 GPU with 32 GB memory. I don't think 10GB is enough for such a large box.

But you can adjust the maximum box size by modifying MAX_NUM_OF_GRID_MI/MAX_NUM_OF_GRID_MJ/MAX_NUM_OF_GRID_MK and MAX_NUM_OF_ATOM_RELATION_COUNT in the kernel2.h file according to your device.

[neru1234]

Hi @Glinttsd,
What is the size limit of small box? My box is 56, 46, 52. It can't dock with "An error occurred: Relation too large! Define a large box (see readme) would help".
Now large box can't work on PC. Is there any way to dock my size?
my gpu

+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.113.01             Driver Version: 535.113.01   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| 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 4060 Ti     Off | 00000000:01:00.0  On |                  N/A |
|  0%   37C    P5               9W / 165W |    940MiB / 16380MiB |     26%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

[ynuozhang]

Hi, the large box is tested in the enviroment of V100 GPU with 32 GB memory. I don't think 10GB is enough for such a large box.

But you can adjust the maximum box size by modifying MAX_NUM_OF_GRID_MI/MAX_NUM_OF_GRID_MJ/MAX_NUM_OF_GRID_MK and MAX_NUM_OF_ATOM_RELATION_COUNT in the kernel2.h file according to your device.

Hi, is there a way to specify the specific GPU local rank to use?