Use float64 add Atomics, Where Available #3172
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@@ Coverage Diff @@
## master #3172 +/- ##
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- Coverage 81.13% 81.1% -0.03%
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Files 384 386 +2
Lines 75077 76398 +1321
Branches 8434 8590 +156
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+ Hits 60915 61964 +1049
- Misses 12874 13114 +240
- Partials 1288 1320 +32 |
sklam
reviewed
Aug 9, 2018
| @@ -812,7 +820,7 @@ def _rebuild(cls, func_reduced, bind, targetoptions, config): | |||
| def __reduce__(self): | |||
| """ | |||
| Reduce the instance for serialization. | |||
| Compiled definitions are serialized in PTX form. | |||
| Compiled definitions are discarded. | |||
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The following tests are failing:
- test_polytyped (numba.cuda.tests.cudapy.test_inspect.TestInspect)
- test_debuginfo_in_asm (numba.cuda.tests.cudapy.test_debuginfo.TestCudaDebugInfo)
- test_environment_override (numba.cuda.tests.cudapy.test_debuginfo.TestCudaDebugInfo)
|
@sklam oops, fixed |
CAS operation work on bit types.
sklam
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Aug 30, 2018
stuartarchibald
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Compute Capability cards >= 6.0 support atomic double addition. Use this (instead of numba's CAS-spinning) if available).
@seibert you were right about numba caching LLVM IR globally in an
AutoJitCUDAKernel- this needs to be per-compute capability as numba poly-fills functionality where not available.