Tests fail on Debian stretch with beignet

[vi]

With beignet 1.3.2-1 and CLBlast v1.2.0 it fails multiple tests:

Total Test time (real) = 397.13 sec

The following tests FAILED:
	  5 - clblast_test_xdot (Failed)
	  6 - clblast_test_xdotu (Failed)
	  7 - clblast_test_xdotc (Failed)
	  8 - clblast_test_xnrm2 (Failed)
	  9 - clblast_test_xasum (Failed)
	 12 - clblast_test_xgbmv (OTHER_FAULT)
	 34 - clblast_test_xgemm (OTHER_FAULT)
	 37 - clblast_test_xsyrk (Failed)
	 38 - clblast_test_xherk (Failed)
	 39 - clblast_test_xsyr2k (Failed)
	 40 - clblast_test_xher2k (Failed)
	 46 - clblast_test_xgemmbatched (OTHER_FAULT)

Additionally matmul build with NETLIB CLBlast fails multiplication if matrix is big enough:

$ ./matmul_cl -n 191 -a 6
...
Central cell: 42.8968
$ ./matmul_cl -n 192 -a 6
...
Central cell: 0

On master branch it also fails.

[CNugteren]

Thanks for reporting. Could you give a bit more info though? Which device are you testing on? And can you post the results of the failing test runs?

[vi]

Lenovo Thinkpad X230. Linux vi-notebook 4.9.33-grsec-64+ #85 SMP PREEMPT Sat Jul 15 00:47:47 +03 2017 x86_64 GNU/Linux 00:02.0 VGA compatible controller: Intel Corporation 3rd Gen Core processor Graphics Controller (rev 09)

How do I get those results? Is it just the terminal output?

[CNugteren]

Would be helpful to run clinfo or the included clblast_test_diagnostics tool to get the name of your device (e.g. HD Graphics Haswell Ultrabook GT2 Mobile).

CMake just runs the test executables, but stores the output somewhere else. You can probably find that in subfolders on disk. Consult the CMake/CTest documentation to get more info. Otherwise, you can just manually run the test executables, e.g. ./clblast_test_xaxpy.

[vi]

Number of platforms                               1
  Platform Name                                   Intel Gen OCL Driver
  Platform Vendor                                 Intel
  Platform Version                                OpenCL 2.0 beignet 1.3
  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_byte_addressable_store cl_khr_3d_image_writes cl_khr_image2d_from_buffer cl_khr_depth_images cl_khr_spir cl_khr_icd cl_intel_accelerator cl_intel_subgroups cl_intel_subgroups_short cl_khr_gl_sharing
  Platform Extensions function suffix             Intel

  Platform Name                                   Intel Gen OCL Driver
Number of devices                                 1
  Device Name                                     Intel(R) HD Graphics IvyBridge M GT2
  Device Vendor                                   Intel
  Device Vendor ID                                0x8086
  Device Version                                  OpenCL 1.2 beignet 1.3
  Driver Version                                  1.3
  Device OpenCL C Version                         OpenCL C 1.2 beignet 1.3
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               16
  Max clock frequency                             1000MHz
  Device Partition                                (core)
    Max number of sub-devices                     1
    Supported partition types                     None, None, None
  Max work item dimensions                        3
  Max work item sizes                             512x512x512
  Max work group size                             512
  Preferred work group size multiple              16
  Preferred / native vector sizes                 
    char                                                16 / 8       
    short                                                8 / 8       
    int                                                  4 / 4       
    long                                                 2 / 2       
    half                                                 0 / 8        (n/a)
    float                                                4 / 4       
    double                                               0 / 2        (n/a)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    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         (n/a)
  Address bits                                    32, Little-Endian
  Global memory size                              2147483648 (2GiB)
  Error Correction support                        No
  Max memory allocation                           1610612736 (1.5GiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        8192
  Global Memory cache line                        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                 2048 images
    Base address alignment for 2D image buffers   4096 bytes
    Pitch alignment for 2D image buffers          1 bytes
    Max 2D image size                             8192x8192 pixels
    Max 3D image size                             8192x8192x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Local
  Local memory size                               65536 (64KiB)
  Max constant buffer size                        134217728 (128MiB)
  Max number of constant args                     8
  Max size of kernel argument                     1024
  Queue properties                                
    Out-of-order execution                        No
    Profiling                                     Yes
  Prefer user sync for interop                    Yes
  Profiling timer resolution                      80ns
  Execution capabilities                          
    Run OpenCL kernels                            Yes
    Run native kernels                            Yes
    SPIR versions                                 1.2
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels                                __cl_copy_region_align4;__cl_copy_region_align16;__cl_cpy_region_unalign_same_offset;__cl_copy_region_unalign_dst_offset;__cl_copy_region_unalign_src_offset;__cl_copy_buffer_rect;__cl_copy_image_1d_to_1d;__cl_copy_image_2d_to_2d;__cl_copy_image_3d_to_2d;__cl_copy_image_2d_to_3d;__cl_copy_image_3d_to_3d;__cl_copy_image_2d_to_buffer;__cl_copy_image_3d_to_buffer;__cl_copy_buffer_to_image_2d;__cl_copy_buffer_to_image_3d;__cl_fill_region_unalign;__cl_fill_region_align2;__cl_fill_region_align4;__cl_fill_region_align8_2;__cl_fill_region_align8_4;__cl_fill_region_align8_8;__cl_fill_region_align8_16;__cl_fill_region_align128;__cl_fill_image_1d;__cl_fill_image_1d_array;__cl_fill_image_2d;__cl_fill_image_2d_array;__cl_fill_image_3d;block_motion_estimate_intel;
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  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_byte_addressable_store cl_khr_3d_image_writes cl_khr_image2d_from_buffer cl_khr_depth_images cl_khr_spir cl_khr_icd cl_intel_accelerator cl_intel_subgroups cl_intel_subgroups_short cl_khr_gl_sharing cl_intel_motion_estimation

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Intel Gen OCL Driver
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [Intel]
  clCreateContext(NULL, ...) [default]            Success [Intel]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (1)
    Platform Name                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics IvyBridge M GT2
  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                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics IvyBridge M GT2

ICD loader properties
  ICD loader Name                                 OpenCL ICD Loader
  ICD loader Vendor                               OCL Icd free software
  ICD loader Version                              2.2.11
  ICD loader Profile                              OpenCL 2.1

* Options given/available:
    -platform 0 [=default]
    -device 0 [=default]


 --- OpenCL device naming:
* Device type                   GPU
* Device name                   Intel(R) HD Graphics IvyBridge M GT2
* Platform vendor               Intel
* Platform version              OpenCL 2.0 beignet 1.3

 --- CLBlast device naming:
* Device type                   GPU
* Device name                   Intel(R) HD Graphics IvyBridge M GT2
* Device vendor                 Intel
* Device architecture           

 --- OpenCL device properties:
* Max work group size           512
* Max work item dimensions      3
* - Max work item size #0       512
* - Max work item size #1       512
* - Max work item size #2       512
* Local memory size             65536KB
* 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_byte_addressable_store cl_khr_3d_image_writes cl_khr_image2d_from_buffer cl_khr_depth_images cl_khr_spir cl_khr_icd cl_intel_accelerator cl_intel_subgroups cl_intel_subgroups_short cl_khr_gl_sharing cl_intel_motion_estimation

 --- Some OpenCL library benchmarks (functions from clpp11.h):
* queue.GetContext()            0.0003 ms
* queue.GetDevice()             0.0002 ms
* device.Name()                 0.0002 ms
* device.Vendor()               0.0001 ms
* device.Version()              0.0002 ms
* device.Platform()             0.0001 ms
* Buffer<float>(context, 1024)  0.0071 ms

$ DISPLAY= ./clblast_test_xaxpy

* Options given/available:
    -platform 0 [=default]
    -device 0 [=default]
    -full_test [false]
    -verbose [false]
    -cblas 1 [=default]

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'SAXPY' routine. Legend:
   : -> Test produced correct results
   . -> Test returned the correct error code
   X -> Test produced incorrect results
   / -> Test returned an incorrect error code
   \ -> Test not executed: OpenCL-kernel compilation error
   o -> Test not executed: Unsupported precision
   - -> Test not completed: Reference CBLAS doesn't output error codes
* Testing with error margins of 0.5% (relative) and 0.001 (absolute)
* Testing 'regular behaviour' for 'default':
   ::::::::::::::::::::::::::::::::::::
   Pass rate 100.0%: 36 passed / 0 skipped / 0 failed
* Completed all test-cases for this routine. Results:
   36 test(s) passed
   0 test(s) skipped
   0 test(s) failed

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'DAXPY' routine.
* All tests skipped: Unsupported precision

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'CAXPY' routine. Legend:
   : -> Test produced correct results
   . -> Test returned the correct error code
   X -> Test produced incorrect results
   / -> Test returned an incorrect error code
   \ -> Test not executed: OpenCL-kernel compilation error
   o -> Test not executed: Unsupported precision
   - -> Test not completed: Reference CBLAS doesn't output error codes
* Testing with error margins of 0.5% (relative) and 0.001 (absolute)
* Testing 'regular behaviour' for 'default':
   ::::::::::::::::::::::::::::::::::::
   Pass rate 100.0%: 36 passed / 0 skipped / 0 failed
* Completed all test-cases for this routine. Results:
   36 test(s) passed
   0 test(s) skipped
   0 test(s) failed

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'ZAXPY' routine.
* All tests skipped: Unsupported precision

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'HAXPY' routine.
* All tests skipped: Unsupported precision

$ DISPLAY= ./clblast_test_xdot

* Options given/available:
    -platform 0 [=default]
    -device 0 [=default]
    -full_test [false]
    -verbose [false]
    -cblas 1 [=default]

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'SDOT' routine. Legend:
   : -> Test produced correct results
   . -> Test returned the correct error code
   X -> Test produced incorrect results
   / -> Test returned an incorrect error code
   \ -> Test not executed: OpenCL-kernel compilation error
   o -> Test not executed: Unsupported precision
   - -> Test not completed: Reference CBLAS doesn't output error codes
* Testing with error margins of 0.5% (relative) and 0.001 (absolute)
* Testing 'regular behaviour' for 'default':
   XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
   Error rate 100.00%: n=7 incx=1 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=1 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=1 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=2 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=2 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=2 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=7 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=7 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=7 incx=7 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=1 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=1 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=1 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=2 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=2 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=2 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=7 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=7 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=93 incx=7 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=1 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=1 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=1 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=2 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=2 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=2 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=7 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=7 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=144 incx=7 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=1 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=1 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=1 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=2 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=2 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=2 incy=7 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=7 incy=1 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=7 incy=2 offx=0 offy=0 offdot=0 
   Error rate 100.00%: n=4096 incx=7 incy=7 offx=0 offy=0 offdot=0 
   Pass rate   0.0%: 0 passed / 0 skipped / 36 failed
* Completed all test-cases for this routine. Results:
   0 test(s) passed
   0 test(s) skipped
   36 test(s) failed

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'DDOT' routine.
* All tests skipped: Unsupported precision

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'HDOT' routine.
* All tests skipped: Unsupported precision

[vi]

Can CLBlast fall back to usual OpenBLAS for unsupported operations by the way?

[CNugteren]

OK thanks, probably Intel(R) HD Graphics IvyBridge M GT2 was sufficient info though ;-) Could you post the output of all failing tests? Either as attachment or as Gist/Pastebin, because otherwise this issue becomes a bit unreadable.

Can CLBlast fall back to usual OpenBLAS for unsupported operations by the way?

What do you mean exactly? And which routines? Are you using the Netlib API by the way instead of the OpenCL API? That's not recommended for speed as you might already know, definitely not on small GPUs such as the Intel GPU you have.

But anyway, let's fix the tests first. One thing you can try is to run the tuners (see README), because perhaps the defaults are not suitable for your particular GPU? I've tested on other Intel GPUs with Beignet with succes.

[vi]

What do you mean exactly? And which routines?

I see messages in tests about failed operations because of missing features in GPU ("Unsupported precision" such as double or half floats). With Netlib API I expect all GPU details to be fully abstracted from user application, but this dependance on GPU features with exceptions in case of missing things is abstraction leak. A proper way would be fall back to CPU implementation if GPU can't do something. I don't know which exact routines (never programmed for BLAS so far), but I expect CLBlast with Netlib API to be drop-in replacement for OpenBLAS (or something like that). It may even include cblas.h or even be ABI-compatible with OpenBLAS, so that existing programs may LD_PRELOAD CLBlast and receive the GPU speedup even without recompilation.

---

Could you post the output of all failing tests?

for i in clblast_test_*; do echo $i; DISPLAY= ./$i; echo $?; done &> log ?

[vi]

Tried tuning (log and jsons), but the python script fails afterwards:

$ python ../scripts/database/database.py . ..
[database] Downloading database from 'https://raw.githubusercontent.com/CNugteren/CLBlast-database/master/database.json'...
[database] Loading database from '../scripts/database/database.json'
[database] Processing './clblast_copy_32.json' with 128 new items
[database] Processing './clblast_routine_gemm_32.json' with 31 new items
[database] Processing './clblast_xger_32.json' with 108 new items
[database] Processing './clblast_xdot_2_32.json' with 5 new items
[database] Processing './clblast_padtranspose_32.json' with 14 new items
[database] Processing './clblast_xgemm_direct_2_32.json' with 125 new items
[database] Processing './clblast_xaxpy_32.json' with 64 new items
[database] Processing './clblast_xgemm_2_32.json' with 229 new items
[database] Processing './clblast_xgemv_fast_32.json' with 30 new items
[database] Processing './clblast_xdot_1_32.json' with 5 new items
[database] Processing './clblast_xgemv_fast_rot_32.json' with 68 new items
[database] Processing './clblast_xgemm_direct_1_32.json' with 45 new items
[database] Processing './clblast_xgemv_32.json' with 12 new items
[database] Processing './clblast_pad_32.json' with 72 new items
[database] Processing './clblast_transpose_32.json' with 48 new items
[database] Processing './clblast_xgemm_1_32.json' with 560 new items
[database] Saving database to '../scripts/database/database.json'
[database] Calculating the best results per device/kernel...
[database] Calculating the default values...
[database] Producing a C++ database in '../src/database/kernels'...
Traceback (most recent call last):
  File "../scripts/database/database.py", line 154, in <module>
    main(sys.argv[1:])
  File "../scripts/database/database.py", line 148, in main
    clblast.print_cpp_database(database_best_results, cpp_database_path)
  File "/mnt/src/git/CLBlast/scripts/database/database/clblast.py", line 177, in print_cpp_database
    assert len(kernel_database) == 1
AssertionError

[sivagnanamn]

@vi To get rid of the python error, delete the ../scripts/database/database.json file and re-run the python script. It'll download a new copy of database.json again & should work without any errors.

[CNugteren]

Thanks for sharing the output of the tests! A quick glance shows that it might be just the reduce and matrix-multiplication kernels failing, they are used in quite a few cases. Let's first see if the tuning can fix them.

To get rid of the python error, delete the ../scripts/database/database.json file and re-run the python script. It'll download a new copy of database.json again & should work without any errors.

Don't think that's going to work, since he just got a fresh copy anyway.

Tried tuning (log and jsons), but the python script fails afterwards.

OK, thanks for sharing the JSONs. I'll take a look myself this weekend at what's going wrong and I'll try to fix it and make the error message more meaningful for future cases. I'll report back as soon as I have something for you.

I expect CLBlast with Netlib API to be drop-in replacement for OpenBLAS (or something like that). It may even include cblas.h or even be ABI-compatible with OpenBLAS, so that existing programs may LD_PRELOAD CLBlast and receive the GPU speedup even without recompilation.

I understand your point, but that might be less trivial to implement than you suggest it. First of all, you'll have to query OpenCL to see what's supported and what not. Then, you'll have to call a BLAS routine, which is not trivial to do since CLBlast also uses cblas.h for that case. But then you'll need all the extra logic to make sure this runs on any platform with any CPU BLAS, and you'll need proper testing. However, even after doing all that, the Netlib API of CLBlast is only useful if you think about speed before using it, e.g. an AXPY operation will be slower due to memory copying overhead. Even an GEMM operation might be slower. So ideally you'll want to decision making per machine/routine/parameters. My conclusion here is that it will take too much effort to make the drop-in Netlib API of CLBlast useful in the sense that you describe it. And since it's not the main/recommended API, I will not be able to work on this in the foreseeable future, but I'll accept pull requests of course.

[CNugteren]

OK, I've just tested with your JSON files (thanks again for sharing), and I didn't encounter any issue. So it is likely that some things changed in the database in the meantime since the release of CLBlast v1.2.0. So there are two things you could do:

• Replace scripts/database/database.json with a corresponding v1.2.0 version from the CLBlast-database repository, direct download link here.
• Or (perhaps better), check out the latest master branch of CLBlast. For your convenience, I have just added the tuning results as well, so with the latest master you can direct re-compile and re-run the tests, hopefully more will now pass. Not sure though, but it is worth trying first before going on.

[vi]

1. Checked out the master (7aabeb4)
2. Re-run the script: [database] All done.
3. Checked git diff - 26 chunks
4. Re-compile: ninja - 195 targets
5. Re-test: ninja test

The following tests FAILED:
	  5 - clblast_test_xdot (Failed)
	  6 - clblast_test_xdotu (Failed)
	  7 - clblast_test_xdotc (Failed)
	  8 - clblast_test_xnrm2 (Failed)
	  9 - clblast_test_xasum (Failed)
	 12 - clblast_test_xgbmv (OTHER_FAULT)
	 34 - clblast_test_xgemm (OTHER_FAULT)
	 37 - clblast_test_xsyrk (Failed)
	 38 - clblast_test_xherk (Failed)
	 39 - clblast_test_xsyr2k (Failed)
	 40 - clblast_test_xher2k (Failed)
	 46 - clblast_test_xgemmbatched (OTHER_FAULT)
	 48 - clblast_test_preprocessor (OTHER_FAULT)

6. Revert what database.py done: git reset --hard.
7. Re-build ninja - 53 targets
8. Re-test: ninja test

Same running time, same Faileds, same OTHER_FAULTs.

[CNugteren]

OK, thanks for testing. Let's first try to resolve the OTHER_FAULT issues, and then later the one that report regular correctness issues. For three of those (GBMV, GEMM, and GEMMBATCHED), I see quite curious output, e.g.:

* Running on OpenCL device 'Intel(R) HD Graphics IvyBridge M GT2'.
* Starting tests for the 'SGBMV' routine. Legend:
   : -> Test produced correct results
   . -> Test returned the correct error code
   X -> Test produced incorrect results
   / -> Test returned an incorrect error code
   \ -> Test not executed: OpenCL-kernel compilation error
   o -> Test not executed: Unsupported precision
   - -> Test not completed: Reference CBLAS doesn't output error codes
* Testing with error margins of 0.5% (relative) and 0.001 (absolute)
* Testing 'regular behaviour' for '101 (row-major) 111 (regular)':
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::
   Pass rate 100.0%: 288 passed / 0 skipped / 0 failed
* Testing 'regular behaviour' for '101 (row-major) 112 (transposed)':
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::
   Pass rate 100.0%: 288 passed / 0 skipped / 0 failed
* Testing 'regular behaviour' for '102 (col-major) 111 (regular)':
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::
   Pass rate 100.0%: 288 passed / 0 skipped / 0 failed
* Testing 'regular behaviour' for '102 (col-major) 112 (transposed)':
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
   ::::::::::::::::::::::::::::beignet-opencl-icd: no supported GPU found, this is probably the wrong opencl-icd package for this hardware
(If you have multiple ICDs installed and OpenCL works, you can ignore this message)
terminate called after throwing an instance of 'clblast::CLCudaAPIError'
  what():  OpenCL error: clGetDeviceIDs: -1
Aborted

This error message is from Beignet, not from CLBlast. It suddenly cannot find your device anymore, which is strange. This seems to suggest something is wrong with your OpenCL set-up, or there is perhaps a bug in beignet? I could not find any issue on the Beignet Bugzilla tracker, but perhaps you can search and file one? First also check if it is reproducible, i.e. does it always fail at exactly the same test?

Then there is another issue with clblast_test_preprocessor it seems, but this seems to be a linker issue. I can't reproduce that myself on a Debian 9 / beignet system, tried with Clang and GCC, but both seem to work fine. Which compiler are you using?

[vi]

Shall I try downgrading beignet to v1.2?