The `memset` function and bitwise manipulation only apply to POD types
that do not require initialization, otherwise resulting in UB. We currently
violate this in `ptrue` and `pzero`, we assume bitmasks for `pselect`, and
bitwise operations are applied byte-by-byte in the generic implementations.
This is causing issues for scalar types that do require initialization
or that contain non-POD info such as pointers (#2201). We either break
them, or force specializations of these functions for custom scalars,
even if they are not vectorized.
Here we modify these functions for scalars only - instead using only
scalar operations:
- `pzero`: `Scalar(0)` for all scalars.
- `ptrue`: `Scalar(1)` for non-trivial scalars, bitset to one bits for trivial scalars.
- `pselect`: ternary select comparing mask to `Scalar(0)` for all scalars
- `pand`, `por`, `pxor`, `pnot`: use operators `&`, `|`, `^`, `~` for all integer or non-trivial scalars, otherwise apply bytewise.
For non-scalar types, the original implementations are used to maintain
compatibility and minimize the number of changes.
Fixes#2201.
With !406, we accidentally broke arm 32-bit NEON builds, since
`vsqrt_f32` is only available for 64-bit.
Here we add back the `rsqrt` implementation for 32-bit, relying
on a `prsqrt` implementation with better handling of edge cases.
Note that several of the 32-bit NEON packet tests are currently
failing - either due to denormal handling (NEON versions flush
to zero, but scalar paths don't) or due to accuracy (e.g. sin/cos).
The previous implementations produced garbage values if the exponent did
not fit within the exponent bits. See #2131 for a complete discussion,
and !375 for other possible implementations.
Here we implement the 4-factor version. See `pldexp_impl` in
`GenericPacketMathFunctions.h` for a full description.
The SSE `pcmp*` methods were moved down since `pcmp_le<Packet4i>`
requires `por`.
Left as a "TODO" is to delegate to a faster version if we know the
exponent does fit within the exponent bits.
Fixes#2131.
Unfortunately `std::bit_and` and the like are host-only functions prior
to c++14 (since they are not `constexpr`). They also never exist in the
global namespace, so the current implementation always fails to compile via
NVCC - since `EIGEN_USING_STD` tries to import the symbol from the global
namespace on device.
To overcome these limitations, we implement these functionals here.
The recent addition of vectorized pow (!330) relies on `pfrexp` and
`pldexp`. This was missing for `Eigen::half` and `Eigen::bfloat16`.
Adding tests for these packet ops also exposed an issue with handling
negative values in `pfrexp`, returning an incorrect exponent.
Added the missing implementations, corrected the exponent in `pfrexp1`,
and added `packetmath` tests.
For these to exist we would need to define `_USE_MATH_DEFINES` before
`cmath` or `math.h` is first included. However, we don't
control the include order for projects outside Eigen, so even defining
the macro in `Eigen/Core` does not fix the issue for projects that
end up including `<cmath>` before Eigen does (explicitly or transitively).
To fix this, we define `EIGEN_LOG2E` and `EIGEN_LN2` ourselves.
The `half_float` test was failing with `-mcpu=cortex-a55` (native `__fp16`) due
to a bad NaN bit-pattern comparison (in the case of casting a float to `__fp16`,
the signaling `NaN` is quieted). There was also an inconsistency between
`numeric_limits<half>::quiet_NaN()` and `NumTraits::quiet_NaN()`. Here we
correct the inconsistency and compare NaNs according to the IEEE 754
definition.
Also modified the `bfloat16_float` test to match.
Tested with `cortex-a53` and `cortex-a55`.
The following commit seems to have introduced regressions in ROCm/HIP support.
183a208212
It causes some unit-tests to fail with the following error
```
...
Eigen/src/Core/GenericPacketMath.h:322:3: error: no member named 'bit_and' in the global namespace; did you mean 'std::bit_and'?
...
Eigen/src/Core/GenericPacketMath.h:329:3: error: no member named 'bit_or' in the global namespace; did you mean 'std::bit_or'?
...
Eigen/src/Core/GenericPacketMath.h:336:3: error: no member named 'bit_xor' in the global namespace; did you mean 'std::bit_xor'?
...
```
The error occurs because, when compiling the device code in HIP/CUDA, the compiler will pick up the some of the std functions (whose calls are prefixed by EIGEN_USING_STD) from the global namespace (i.e. use ::bit_xor instead of std::bit_xor). For this to work, those functions must be declared in the global namespace in the HIP/CUDA header files. The `bit_and`, `bit_or` and `bit_xor` routines are not declared in the HIP header file that contain the decls for the std math functions ( `math_functions.h` ), and this is the cause of the error above.
It seems that the newer HIP compilers do support the calling of `std::` math routines within device code, and the ideal fix here would have been to change all calls to std math functions in EIGEN to use the `std::` namespace (instead of the global namespace ), when compiling with HIP compiler. However it seems there was a recent commit to remove the EIGEN_USING_STD_MATH macro and collapse it uses into the EIGEN_USING_STD macro ( 4091f6b25c ).
Replacing all std math calls will essentially require re-surrecting the EIGEN_USING_STD_MATH macro, so not choosing that option.
Also HIP compilers only have support std math calls within device code, and not all std functions (specifically not for malloc/free which are prefixed via EIGEN_USING_STD). So modyfing EIGEN_USE_STD implementation to use std:: namspace for HIP will not work either.
Hence going for the ugly solution of special casing the three calls that breaking the HIP compile, to explicitly use the std:: namespace
The NEON `pcast` operators are all implemented and tested for existing
packets. This requires adding a `pcast(a,b,c,d,e,f,g,h)` for casting
between `int64_t` and `int8_t` in `GenericPacketMath.h`.
Removed incorrect `HasHalfPacket` definition for NEON's
`Packet2l`/`Packet2ul`.
Adjustments were also made to the `packetmath` tests. These include
- minor bug fixes for cast tests (i.e. 4:1 casts, only casting for
packets that are vectorizable)
- added 8:1 cast tests
- random number generation
- original had uninteresting 0 to 0 casts for many casts between
floating-point and integers, and exhibited signed overflow
undefined behavior
Tested:
```
$ aarch64-linux-gnu-g++ -static -I./ '-DEIGEN_TEST_PART_ALL=1' test/packetmath.cpp -o packetmath
$ adb push packetmath /data/local/tmp/
$ adb shell "/data/local/tmp/packetmath"
```
The use of the `packet_traits<>::HasCast` field is currently inconsistent with
`type_casting_traits<>`, and is unused apart from within
`test/packetmath.cpp`. In addition, those packetmath cast tests do not
currently reflect how casts are performed in practice: they ignore the
`SrcCoeffRatio` and `TgtCoeffRatio` fields, assuming a 1:1 ratio.
Here we remove the unsed `HasCast`, and modify the packet cast tests to
better reflect their usage.
This change also contains a few minor cleanups:
1. Remove packet op pnot, which is not needed for anything other than pcmp_le_or_nan,
which can be done in other ways.
2. Remove the "HasInsert" enum, which is no longer needed since we removed the
corresponding packet ops.
3. Add faster pselect op for Packet4i when SSE4.1 is supported.
Among other things, this makes the fast transposeInPlace() method available for Matrix<bool>.
Run on ************** (72 X 2994 MHz CPUs); 2020-05-09T10:51:02.372347913-07:00
CPU: Intel Skylake Xeon with HyperThreading (36 cores) dL1:32KB dL2:1024KB dL3:24MB
Benchmark Time(ns) CPU(ns) Iterations
-----------------------------------------------------------------------
BM_TransposeInPlace<float>/4 9.77 9.77 71670320
BM_TransposeInPlace<float>/8 21.9 21.9 31929525
BM_TransposeInPlace<float>/16 66.6 66.6 10000000
BM_TransposeInPlace<float>/32 243 243 2879561
BM_TransposeInPlace<float>/59 844 844 829767
BM_TransposeInPlace<float>/64 933 933 750567
BM_TransposeInPlace<float>/128 3944 3945 177405
BM_TransposeInPlace<float>/256 16853 16853 41457
BM_TransposeInPlace<float>/512 204952 204968 3448
BM_TransposeInPlace<float>/1k 1053889 1053861 664
BM_TransposeInPlace<bool>/4 14.4 14.4 48637301
BM_TransposeInPlace<bool>/8 36.0 36.0 19370222
BM_TransposeInPlace<bool>/16 31.5 31.5 22178902
BM_TransposeInPlace<bool>/32 111 111 6272048
BM_TransposeInPlace<bool>/59 626 626 1000000
BM_TransposeInPlace<bool>/64 428 428 1632689
BM_TransposeInPlace<bool>/128 1677 1677 417377
BM_TransposeInPlace<bool>/256 7126 7126 96264
BM_TransposeInPlace<bool>/512 29021 29024 24165
BM_TransposeInPlace<bool>/1k 116321 116330 6068
