Hi,
I have tried using NPU in Vim3 basic with OpenCL libraries. By changing the symbolic links, I could get the following in clinfo:
$ clinfo
Number of platforms 1
Platform Name Vivante OpenCL Platform
Platform Vendor Vivante Corporation
Platform Version OpenCL 3.0 V6.4.8.7.415784
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_il_program cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
Platform Host timer resolution 0ns
Platform Name Vivante OpenCL Platform
Number of devices 1
Device Name Vivante OpenCL Device VIPNano-QI.7120.0000
Device Vendor Vivante Corporation
Device Vendor ID 0x564956
Device Version OpenCL 3.0
Driver Version OpenCL 3.0 V6.4.8.7.415784
Device OpenCL C Version OpenCL C 1.2
Device Type GPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 1
Max clock frequency 800MHz
Device Partition (core)
Max number of sub-devices 0
Supported partition types None
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 256x256x256
Max work group size 256
Preferred work group size multiple 4
Max sub-groups per work group 0
Preferred / native vector sizes
char 4 / 4
short 4 / 4
int 4 / 4
long 4 / 4
half 4 / 4 (cl_khr_fp16)
float 4 / 4
double 0 / 0 (n/a)
Half-precision Floating-point support (cl_khr_fp16)
Denormals No
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Single-precision Floating-point support (core)
Denormals No
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Correctly-rounded divide and sqrt operations No
Double-precision Floating-point support (n/a)
Address bits 32, Little-Endian
Global memory size 268435456 (256MiB)
Error Correction support Yes
Max memory allocation 134217728 (128MiB)
Unified memory for Host and Device Yes
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing No
Fine-grained buffer sharing No
Fine-grained system sharing No
Atomics No
Minimum alignment for any data type 128 bytes
Alignment of base address 2048 bits (256 bytes)
Preferred alignment for atomics
SVM 0 bytes
Global 0 bytes
Local 0 bytes
Max size for global variable 0
Preferred total size of global vars 0
Global Memory cache type Read/Write
Global Memory cache size 16384 (16KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 16
Max size for 1D images from buffer 65536 pixels
Max 1D or 2D image array size 8192 images
Max 2D image size 8192x8192 pixels
Max 3D image size 8192x8192x8192 pixels
Max number of read image args 128
Max number of write image args 8
Max number of read/write image args 0
Max number of pipe args 0
Max active pipe reservations 0
Max pipe packet size 0
Local memory type Global
Local memory size 32768 (32KiB)
Max number of constant args 9
Max constant buffer size 65536 (64KiB)
Max size of kernel argument 1024
Queue properties (on host)
Out-of-order execution Yes
Profiling Yes
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 1000ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Sub-group independent forward progress No
IL version SPIR-V_1.5
printf() buffer size 1048576 (1024KiB)
Built-in kernels (n/a)
Device Extensions cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_il_program cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) Success [P0]
clCreateContext(NULL, ...) [default] Success [P0]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) Success (1)
Platform Name Vivante OpenCL Platform
Device Name Vivante OpenCL Device VIPNano-QI.7120.0000
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) Success (1)
Platform Name Vivante OpenCL Platform
Device Name Vivante OpenCL Device VIPNano-QI.7120.0000
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 Vivante OpenCL Platform
Device Name Vivante OpenCL Device VIPNano-QI.7120.0000
NOTE: your OpenCL library only supports OpenCL 2.2,
but some installed platforms support OpenCL 3.0.
Programs using 3.0 features may crash
or behave unexpectedly
I could run some OpenCL application for matrix manipulation which worked fine as well. Still, when I tried to run Tensorflow benchmark tool, the latency seem to have increased way too much (0.5-1 FPS) in comparison with the GPU - 10 FPS! Also, with some of the models (such as Mediapipe BlazePose), I got the following error corresponding to CL_BUILD_PROGRAM _FAILURE:
ERROR: Failed to build program executable - Build program failure(82:0) : error : syntax error at ‘[’
(82:0) : error : syntax error at ‘[’
The tool used with both OpenCL-GPU and OpenCL-NPU are the same with only difference being the backend - OpenCL libraries and the NPU.
- Could you please clarify if the OpenCL support for NPU on Vim3 is intact?
- Is there any sort of limitation OpenCL support for Vivante NPU causing this poor performance?