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As the test has worked for 256 and 1,000 dimensions, the problem probably is that your GPU has not enough memory to run a 10,000 dimension SDM. It happened in my MacBook Pro, for instance.
I'll let this issue opened to improve the error message.
AL$ ./test1
Dimension: 256
Number of hardlocations: 1000000
Allocated memory for addresses: 30.5 MB
Allocated bits per bitstring: 256
Remaining bits per bitstring: 0
Memory efficiency: 100.0%
bs1 = 960856d47a366b8ea73355070440c184efdec8b1c58981e7264a966ed770a674
@@ Linear 1055
@@ Thread 1055
@@ Linear2 1055
@@ Thread2 1055
OpenCL platforms: 1 devices: 1
OpenCL Max compute units=48 Default kernel=single_scan5_unroll Local worksize=4 Global worksize=50304
@@ OpenCL2 1055
Dimension: 1000
Number of hardlocations: 1000000
Allocated memory for addresses: 122.1 MB
Allocated bits per bitstring: 1024
Remaining bits per bitstring: 24
Memory efficiency: 97.7%
bs1 = 6f73b58020731efdc43d1131b1d62afe51e948c2ab1faeb2da1959bcb75d9684adff69a28942eb4ad7b96c1ffcc8b15f6a7b2d491acb48b16b86d1fb278da7a12f0f0a7642216a11caddbacf608461e72baa388a03d12cf5a1788e8fb1935fa12a7ca2ff7992a5e3f6363c0a80426b745afa551aec8d82e6d9525ce1a0000000
@@ Linear 1043
@@ Thread 1043
@@ Linear2 1043
@@ Thread2 1043
OpenCL platforms: 1 devices: 1
OpenCL Max compute units=48 Default kernel=single_scan5_unroll Local worksize=16 Global worksize=50688
@@ OpenCL2 1043
Dimension: 10000
Number of hardlocations: 1000000
Allocated memory for addresses: 1197.8 MB
Allocated bits per bitstring: 10048
Remaining bits per bitstring: 48
Memory efficiency: 99.5%
bs1 = 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
@@ Linear 984
@@ Thread 984
@@ Linear2 984
@@ Thread2 984
OpenCL platforms: 1 devices: 1
OpenCL Max compute units=48 Default kernel=single_scan5_unroll Local worksize=256 Global worksize=73728
Assertion failed: (error == CL_SUCCESS), function as_scanner_opencl_init, file scanner_opencl.c, line 184.
Abort trap: 6
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