Zhiguo Zhou 8b20e9f505 Vectorize AssociativeGenericApplierImpl::apply (#43669) ... * Vectorize AssociativeGenericApplierImpl::apply This commit achieved the auto-vectorization by redefining numerical values of ternary representations and corresponding implementations of And/Or operators, caching the intermediate ternary values in a continuous range of memory for the SIMD instructions to consume, and removing the short-circuit for the ternary logic evaluation. * Optimize TernaryValueBuilder for ColumnNullable The numerical representation of a ColumnNullable is calculated from the data column of any data type and the null map column of UInt8 with a bitwise operation expression, which is efficient for auto- vectorization. However, when this expression is applied to a data column of a type other than UInt8, the SIMD register is not fully utilized due to the mismatch of data types, and the data throughput regresses. To optimize the SIMD register usage, the has_value flag is firstly evaluated from the data column and stored in a UInt8 array. Then it is loaded from memory before the calculation of bitwise operation expression, so that the types of the operands are both UInt8.		2022-12-15 18:27:19 +01:00
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CMakeLists.txt
gtest_has_all.cpp
gtest_number_traits.cpp
gtest_ternary_logic.cpp	Vectorize AssociativeGenericApplierImpl::apply (#43669)	2022-12-15 18:27:19 +01:00