GPU acceleration support is not available
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评估
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 新手友好度
- 25/100
- Issue 类型
- 缺陷
- 描述清晰度
- 需要澄清
- 活跃度
- 停滞
- 技术栈
- cpp, docker
调研方向
从报告中列出的 oneDNN getting_started、C++SYCL DenseLinearAlgebra/vector-add 和 IntelTensorFlow_Horovod_Distributed_Deep_Learning 示例路径开始。复现 Docker 设置,运行 sycl-ls,并比较 CPU 和 GPU 命令的结果。完成的标准是确定所报告的 Intel GPU 不可用的原因,并记录或修正受影响示例的行为。
由索引模型根据 Issue 内容生成。
描述
Summary
There is an issue where graphics acceleration support for 13th generation Intel CPUs is not available.
Is there a way to verify if GPU acceleration is possible?
Why is my laptop unable to recognize it?
Version
I tested it using the image from https://hub.docker.com/r/intel/oneapi.
Environment
lscpu - click to extand
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 16
On-line CPU(s) list: 0-15
Vendor ID: GenuineIntel
Model name: 13th Gen Intel(R) Core(TM) i7-1360P
CPU family: 6
Model: 186
Thread(s) per core: 2
Core(s) per socket: 12
Socket(s): 1
Stepping: 2
CPU(s) scaling MHz: 31%
CPU max MHz: 5000.0000
CPU min MHz: 400.0000
BogoMIPS: 5222.40
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc ar
t arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16
xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhance
d tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetb
v1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes
vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities
Virtualization features:
Virtualization: VT-x
Caches (sum of all):
L1d: 448 KiB (12 instances)
L1i: 640 KiB (12 instances)
L2: 9 MiB (6 instances)
L3: 18 MiB (1 instance)
NUMA:
NUMA node(s): 1
NUMA node0 CPU(s): 0-15
Vulnerabilities:
Gather data sampling: Not affected
Itlb multihit: Not affected
L1tf: Not affected
Mds: Not affected
Meltdown: Not affected
Mmio stale data: Not affected
Reg file data sampling: Mitigation; Clear Register File
Retbleed: Not affected
Spec rstack overflow: Not affected
Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Srbds: Not affected
Tsx async abort: Not affected
lspci -vvnn | grep "VGA compatible controller" - click to expand
00:02.0 VGA compatible controller [0300]: Intel Corporation Raptor Lake-P [Iris Xe Graphics] [8086:a7a0] (rev 04) (prog-if 00 [VGA controller])
I ran the Docker image with the -it option and proceeded as follows:
cd /
mkdir workspace
cd workspace
git clone https://github.com/oneapi-src/oneAPI-samples.git
Steps to reproduce
I conducted a total of three tests.
1. For the test at https://github.com/oneapi-src/oneAPI-samples/tree/master/Libraries/oneDNN/getting_started:
mkdir build
cd build
cmake ..
make
export DNNL_VERBOSE=1
./bin/getting-started-cpp
Result
onednn_verbose,info,oneDNN v3.5.0 (commit 302c601036103dd8391ac583030abd2e19a75f92)
onednn_verbose,info,cpu,runtime:DPC++,nthr:16
onednn_verbose,info,cpu,isa:Intel AVX2 with Intel DL Boost
onednn_verbose,info,gpu,runtime:DPC++
onednn_verbose,info,cpu,engine,0,backend:OpenCL,name:13th Gen Intel(R) Core(TM) i7-1360P,driver_version:2024.18.6,binary_kernels:disabled
onednn_verbose,info,graph,backend,0:dnnl_backend
onednn_verbose,primitive,info,template:operation,engine,primitive,implementation,prop_kind,memory_descriptors,attributes,auxiliary,problem_desc,exec_time
onednn_verbose,graph,info,template:operation,engine,partition_id,partition_kind,op_names,data_formats,logical_tensors,fpmath_mode,backend,exec_time
onednn_verbose,primitive,exec,cpu,eltwise,jit:avx2,forward_inference,data_f32::blocked:acdb::f0 diff_undef::undef:::,,alg:eltwise_relu alpha:0 beta:0,1x3x13x13,0.231201
Example passed on CPU.
if I run:
./bin/getting-started-cpp gpu
Result
root@e77315b5cda4:/workspace/oneAPI-samples/Libraries/oneDNN/getting_started/build# ./bin/getting-started-cpp gpu
Application couldn't find GPU, please run with CPU instead.
2. For the test at https://github.com/oneapi-src/oneAPI-samples/tree/master/DirectProgramming/C++SYCL/DenseLinearAlgebra/vector-add:
mkdir build
cd build
cmake ..
make spu-gpu
./vector-add-buffers
Result
root@e77315b5cda4:/workspace/oneAPI-samples/DirectProgramming/C++SYCL/DenseLinearAlgebra/vector-add/build# ./vector-add-buffers
Running on device: 13th Gen Intel(R) Core(TM) i7-1360P
Vector size: 10000
[0]: 0 + 0 = 0
[1]: 1 + 1 = 2
[2]: 2 + 2 = 4
...
[9999]: 9999 + 9999 = 19998
Vector add successfully completed on device.
- For the test at https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Features-and-Functionality/IntelTensorFlow_Horovod_Distributed_Deep_Learning:
Even when I run !sycl-ls, only the CPU is listed.
Observed behavior
Cannot find my GPU
Expected behavior
GPU acceleration works
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