terminate called after throwing an instance of 'cl::sycl::invalid_object_error'
huangzhiyuan opened this issue · 6 comments
huangzhiyuan commented
Hi, I have ComputerCPP 1.0.3.
But fails to run any sample Computecpp example and instead throws cl::sycl::invalid_object_error.
clinfo, source code and erro bt are below:
Clinfo
Number of platforms 2
Platform Name Intel(R) OpenCL HD Graphics
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 2.1
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_depth_images cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_icd cl_khr_image2d_from_buffer cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_intel_subgroups cl_intel_required_subgroup_size cl_intel_subgroups_short cl_khr_spir cl_intel_accelerator cl_intel_media_block_io cl_intel_driver_diagnostics cl_intel_device_side_avc_motion_estimation cl_khr_priority_hints cl_khr_throttle_hints cl_khr_create_command_queue cl_khr_fp64 cl_khr_subgroups cl_khr_il_program cl_intel_spirv_device_side_avc_motion_estimation cl_intel_spirv_media_block_io cl_intel_spirv_subgroups cl_khr_spirv_no_integer_wrap_decoration cl_khr_mipmap_image cl_khr_mipmap_image_writes cl_intel_planar_yuv cl_intel_packed_yuv cl_intel_motion_estimation cl_intel_advanced_motion_estimation
Platform Host timer resolution 1ns
Platform Extensions function suffix INTEL
Platform Name Experimental OpenCL 2.1 CPU Only Platform
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 2.1 LINUX
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_icd 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_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer
Platform Host timer resolution 1ns
Platform Extensions function suffix INTEL
Platform Name Intel(R) OpenCL HD Graphics
Number of devices 1
Device Name Intel(R) Gen9 HD Graphics NEO
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 2.1 NEO
Driver Version 19.20.13008
Device OpenCL C Version OpenCL C 2.0
Device Type GPU
Device Profile FULL_PROFILE
Max compute units 24
Max clock frequency 1200MHz
Device Partition (core)
Max number of sub-devices 0
Supported partition types None
Max work item dimensions 3
Max work item sizes 256x256x256
Max work group size 256
Preferred work group size multiple 32
Max sub-groups per work group 32
Preferred / native vector sizes
char 16 / 16
short 8 / 8
int 4 / 4
long 1 / 1
half 8 / 8 (cl_khr_fp16)
float 1 / 1
double 1 / 1 (cl_khr_fp64)
Half-precision Floating-point support (cl_khr_fp16)
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
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
Correctly-rounded divide and sqrt operations No
Address bits 64, Little-Endian
Global memory size 26867843072 (25.02GiB)
Error Correction support No
Max memory allocation 4294959104 (4GiB)
Unified memory for Host and Device Yes
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 1024 bits (128 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 64 bytes
Max size for global variable 65536 (64KiB)
Preferred total size of global vars 4294959104 (4GiB)
Global Memory cache type Read/Write
Global Memory cache size 524288
Global Memory cache line 64 bytes
Image support Yes
Max number of samplers per kernel 16
Max size for 1D images from buffer 268434944 pixels
Max 1D or 2D image array size 2048 images
Base address alignment for 2D image buffers 4 bytes
Pitch alignment for 2D image buffers 4 bytes
Max 2D image size 16384x16384 pixels
Max 3D image size 16384x16384x2048 pixels
Max number of read image args 128
Max number of write image args 128
Max number of read/write image args 128
Max number of pipe args 16
Max active pipe reservations 1
Max pipe packet size 1024
Local memory type Local
Local memory size 65536 (64KiB)
Max constant buffer size 4294959104 (4GiB)
Max number of constant args 8
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 Yes
Profiling Yes
Preferred size 131072 (128KiB)
Max size 67108864 (64MiB)
Max queues on device 1
Max events on device 1024
Prefer user sync for interop Yes
Profiling timer resolution 83ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Sub-group independent forward progress Yes
IL version SPIR-V_1.2
SPIR versions 1.2
printf() buffer size 4194304 (4MiB)
Built-in kernels block_motion_estimate_intel;block_advanced_motion_estimate_check_intel;block_advanced_motion_estimate_bidirectional_check_intel;
Motion Estimation accelerator version (Intel) 2
Device Available Yes
Compiler Available Yes
Linker Available Yes
Device Extensions cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_depth_images cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_icd cl_khr_image2d_from_buffer cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_intel_subgroups cl_intel_required_subgroup_size cl_intel_subgroups_short cl_khr_spir cl_intel_accelerator cl_intel_media_block_io cl_intel_driver_diagnostics cl_intel_device_side_avc_motion_estimation cl_khr_priority_hints cl_khr_throttle_hints cl_khr_create_command_queue cl_khr_fp64 cl_khr_subgroups cl_khr_il_program cl_intel_spirv_device_side_avc_motion_estimation cl_intel_spirv_media_block_io cl_intel_spirv_subgroups cl_khr_spirv_no_integer_wrap_decoration cl_khr_mipmap_image cl_khr_mipmap_image_writes cl_intel_planar_yuv cl_intel_packed_yuv cl_intel_motion_estimation cl_intel_advanced_motion_estimation
Platform Name Experimental OpenCL 2.1 CPU Only Platform
Number of devices 1
Device Name Intel(R) Core(TM) i7-8700K CPU @ 3.70GHz
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 2.1 (Build 10)
Driver Version 1.2.0.10
Device OpenCL C Version OpenCL C 2.0
Device Type CPU
Device Profile FULL_PROFILE
Max compute units 12
Max clock frequency 3700MHz
Device Partition (core)
Max number of sub-devices 12
Supported partition types by counts, equally, by names (Intel)
Max work item dimensions 3
Max work item sizes 8192x8192x8192
Max work group size 8192
Preferred work group size multiple 128
Max sub-groups per work group 1
Preferred / native vector sizes
char 1 / 32
short 1 / 16
int 1 / 8
long 1 / 4
half 0 / 0 (n/a)
float 1 / 8
double 1 / 4 (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 No
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 (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
Correctly-rounded divide and sqrt operations No
Address bits 64, Little-Endian
Global memory size 33584807936 (31.28GiB)
Error Correction support No
Max memory allocation 8396201984 (7.82GiB)
Unified memory for Host and Device Yes
Shared Virtual Memory (SVM) capabilities (core)
Coarse-grained buffer sharing Yes
Fine-grained buffer sharing Yes
Fine-grained system sharing Yes
Atomics Yes
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Preferred alignment for atomics
SVM 64 bytes
Global 64 bytes
Local 0 bytes
Max size for global variable 65536 (64KiB)
Preferred total size of global vars 65536 (64KiB)
Global Memory cache type Read/Write
Global Memory cache size 262144
Global Memory cache line 64 bytes
Image support Yes
Max number of samplers per kernel 480
Max size for 1D images from buffer 524762624 pixels
Max 1D or 2D image array size 2048 images
Base address alignment for 2D image buffers 64 bytes
Pitch alignment for 2D image buffers 64 bytes
Max 2D image size 16384x16384 pixels
Max 3D image size 2048x2048x2048 pixels
Max number of read image args 480
Max number of write image args 480
Max number of read/write image args 480
Max number of pipe args 16
Max active pipe reservations 21845
Max pipe packet size 1024
Local memory type Global
Local memory size 32768 (32KiB)
Max constant buffer size 131072 (128KiB)
Max number of constant args 480
Max size of kernel argument 3840 (3.75KiB)
Queue properties (on host)
Out-of-order execution Yes
Profiling Yes
Local thread execution (Intel) Yes
Queue properties (on device)
Out-of-order execution Yes
Profiling Yes
Preferred size 4294967295 (4GiB)
Max size 4294967295 (4GiB)
Max queues on device 4294967295
Max events on device 4294967295
Prefer user sync for interop No
Profiling timer resolution 1ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels Yes
Sub-group independent forward progress No
IL version SPIR-V_1.0
SPIR versions 1.2
printf() buffer size 1048576 (1024KiB)
Built-in kernels
Device Available Yes
Compiler Available Yes
Linker Available Yes
Device Extensions cl_khr_icd 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_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_fp64 cl_khr_image2d_from_buffer
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 [INTEL]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform
NOTE: your OpenCL library only supports OpenCL 2.0,
but some installed platforms support OpenCL 2.1.
Programs using 2.1 features may crash
or behave unexepectedly
Source code
https://developer.codeplay.com/products/computecpp/ce/guides/sycl-guide/hello-sycl
#include <iostream>
#include <CL/sycl.hpp>
namespace sycl = cl::sycl;
int main() {
sycl::float4 a = {1.0, 2.0, 3.0, 4.0};
sycl::float4 b = {4.0, 3.0, 2.0, 3.0};
sycl::float4 c = {.0, 0.0, 0.0, 0.0};
sycl::default_selector device_selector;
sycl::queue queue(device_selector);
std::cout << "Running on "
<< queue.get_device().get_info<sycl::info::device::name>()
<< "\n";
sycl::buffer<sycl::float4, 1> a_sycl(&a, sycl::range<1>(1));
sycl::buffer<sycl::float4, 1> b_sycl(&b, sycl::range<1>(1));
sycl::buffer<sycl::float4, 1> c_sycl(&c, sycl::range<1>(1));
queue.submit([&] (sycl::handler& cgh) {
auto a_acc = a_sycl.get_access<sycl::access::mode::read>(cgh);
auto b_acc = b_sycl.get_access<sycl::access::mode::read>(cgh);
auto c_acc = c_sycl.get_access<sycl::access::mode::discard_write>(cgh);
cgh.single_task<class vector_addition>([=] () {
c_acc[0] = a_acc[0] + b_acc[0];
});
});
std::cout << " A { " << a.x() << ", " << a.y() << ", " << a.z() << ", " << a.w() << " }\n"
<< "+ B { " << b.x() << ", " << b.y() << ", " << b.z() << ", " << b.w() << " }\n"
<< "------------------\n"
<< "= C { " << c.x() << ", " << c.y() << ", " << c.z() << ", " << c.w() << " }"
<< std::endl;
return 0;
}
Build steps
compute++ -g -I/usr/local/computecpp/include gpu_vector_add.cpp -L/usr/local/computecpp/lib -lComputeCpp -o gpu_vector_add
Runtime error bt
(gdb) r
Starting program: /home/huang/compute/gpu_vector_add
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[New Thread 0x7fff66ca0700 (LWP 13598)]
[New Thread 0x7fff6649f700 (LWP 13599)]
[New Thread 0x7fff65c9e700 (LWP 13600)]
[New Thread 0x7fff64f93700 (LWP 13601)]
Device: Intel(R) Gen9 HD Graphics NEO
terminate called after throwing an instance of 'cl::sycl::invalid_object_error'
Thread 1 "gpu_vector_add" received signal SIGABRT, Aborted.
0x00007ffff67e5428 in __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:54
54 ../sysdeps/unix/sysv/linux/raise.c: No such file or directory.
(gdb) bt
#0 0x00007ffff67e5428 in __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:54
#1 0x00007ffff67e702a in __GI_abort () at abort.c:89
#2 0x00007ffff71348ae in ?? () from /usr/lib/x86_64-linux-gnu/libstdc++.so.6
#3 0x00007ffff71404b6 in ?? () from /usr/lib/x86_64-linux-gnu/libstdc++.so.6
#4 0x00007ffff7140521 in std::terminate() () from /usr/lib/x86_64-linux-gnu/libstdc++.so.6
#5 0x00007ffff7140775 in __cxa_throw () from /usr/lib/x86_64-linux-gnu/libstdc++.so.6
#6 0x00007ffff75ec19f in void cl::sycl::detail::handle_sycl_log<cl::sycl::invalid_object_error>(cl::sycl::detail::sycl_log&&) ()
from /usr/local/computecpp/lib/libComputeCpp.so
#7 0x00007ffff75e57c3 in cl::sycl::detail::trigger_sycl_log(cl::sycl::log_type, char const*, int, int, cl::sycl::detail::cpp_error_code, cl::sycl::detail::context const*, char const*) () from /usr/local/computecpp/lib/libComputeCpp.so
#8 0x0000000000408b97 in cl::sycl::program::create_program_for_kernel<VectorAdd> (c=...) at /usr/local/computecpp/include/SYCL/program.h:446
#9 0x0000000000403ddc in cl::sycl::handler::parallel_for_impl<VectorAdd, main::$_0::operator()(cl::sycl::handler&) const::{lambda(cl::sycl::id<1>)#1}>(cl::sycl::detail::index_array const&, cl::sycl::detail::index_array const, main::$_0::operator()(cl::sycl::handler&) const::{lambda(cl::sycl::id<1>)#1} const&) (this=0x623560, range=...,
globalOffset=..., functor=...) at /usr/local/computecpp/include/SYCL/apis.h:431
#10 0x0000000000403d2a in cl::sycl::handler::parallel_for<VectorAdd, main::$_0::operator()(cl::sycl::handler&) const::{lambda(cl::sycl::id<1>)#1}, 1>(cl::sycl::range<1> const&, main::$_0::operator()(cl::sycl::handler&) const::{lambda(cl::sycl::id<1>)#1} const&) (this=0x623560, range=..., functor=...)
at /usr/local/computecpp/include/SYCL/apis.h:459
#11 0x0000000000403bf9 in main::$_0::operator() (this=0x7fffffffdad0, cgh=...) at gpu_vector_add.cpp:85
#12 0x00000000004039bf in cl::sycl::detail::command_group::submit_handler<main::$_0> (this=0x7fffffffdb88, cgf=...,
fallbackQueue=std::shared_ptr<cl::sycl::detail::queue> (empty) = {...}) at /usr/local/computecpp/include/SYCL/command_group.h:152
#13 0x000000000040381b in cl::sycl::queue::submit<main::$_0> (this=0x6244b0, cgf=...) at /usr/local/computecpp/include/SYCL/queue.h:374
#14 0x0000000000403192 in main (argc=1, args=0x7fffffffe048) at gpu_vector_add.cpp:80
Any help or suggestions is appreciated. ths!
rodburns commented
It should work if you add the flag -sycl-driver to your compile command.
compute++ -g -I/usr/local/computecpp/include gpu_vector_add.cpp -sycl-driver -L/usr/local/computecpp/lib -lComputeCpp -o gpu_vector_add
This will ensure you are compiling for the device.
jwlawson commented
Thanks for the detailed report. As Rod says, it looks like you are not compiling the SYCL kernels for the device, but only compiling the host code. Adding the -sycl-driver flag to compute++ tells the compiler to build the device code as well as the host code, so that the kernels can be found at runtime.
This also highlights an issue with the sample code, that the data will not be copied back to the host. You will need to modify the sample to force the data to be copied. An easy way to do this is to add a scope around the buffers, so that the buffer destructors trigger the copy back:
@@ -16,6 +16,7 @@
<< queue.get_device().get_info<sycl::info::device::name>()
<< "\n";
+ {
sycl::buffer<sycl::float4, 1> a_sycl(&a, sycl::range<1>(1));
sycl::buffer<sycl::float4, 1> b_sycl(&b, sycl::range<1>(1));
sycl::buffer<sycl::float4, 1> c_sycl(&c, sycl::range<1>(1));
@@ -29,6 +30,7 @@
c_acc[0] = a_acc[0] + b_acc[0];
});
});
+ }
std::cout << " A { " << a.x() << ", " << a.y() << ", " << a.z() << ", " << a.w() << " }\n"
<< "+ B { " << b.x() << ", " << b.y() << ", " << b.z() << ", " << b.w() << " }\n"huangzhiyuan commented
DuncanMcBain commented
There is a guide on our website that describes how to integrate ComputeCpp with your code. Generally we recommend the use of our CMake which will make all this work for you.
huangzhiyuan commented
Got it. thanks for your clarification. Now close this issue.