- no FMA: 1ULP up to 3pi, 2ULP up to sin(25966) and cos(18838), fallback to std::sin/cos for larger inputs
- FMA: 1ULP up to sin(117435.992) and cos(71476.0625), fallback to std::sin/cos for larger inputs
Commit c53eececb0
introduced AVX512 support for complex numbers but required
avx512dq to build. Commit 1d683ae2f5
fixed some but not, it would seem all,
of the hard avx512dq dependencies. Build failures are still evident on
Eigen and TensorFlow when compiling with just avx512f and no avx512dq
using gcc 7.3. Looking at the code there does indeed seem to be a problem.
Commit c53eececb0
calls avx512dq intrinsics directly, e.g, _mm512_extractf32x8_ps
and _mm512_and_ps. This commit fixes the issue by replacing the direct
intrinsic calls with the various wrapper functions that are safe to use on
avx512f only builds.
This is a preparation to a change on gebp_traits, where a new template
argument will be introduced to dictate the packet size, so it won't be
bound to the current/max packet size only anymore.
By having packet types defined early on gebp_traits, one has now to
act on packet types, not scalars anymore, for the enum values defined
on that class. One approach for reaching the vectorizable/size
properties one needs there could be getting the packet's scalar again
with unpacket_traits<>, then the size/Vectorizable enum entries from
packet_traits<>. It turns out guards like "#ifndef
EIGEN_VECTORIZE_AVX512" at AVX/PacketMath.h will hide smaller packet
variations of packet_traits<> for some types (and it makes sense to
keep that). In other words, one can't go back to the scalar and create
a new PacketType, as this will always lead to the maximum packet type
for the architecture.
The less costly/invasive solution for that, thus, is to add the
vectorizable info on every unpacket_traits struct as well.
It is based on the SSE version which is much more accurate, though very slightly slower.
This changeset also includes the following required changes:
- add packet-float to packet-int type traits
- add packet float<->int reinterpret casts
- add faster pselect for AVX based on blendv
1. Eigen/src/Core/arch/GPU/Half.h
Updating the HIPCC implementation half so that it can declared as a __shared__ variable
2. Eigen/src/Core/util/Macros.h, Eigen/src/Core/util/Memory.h
introducing a EIGEN_USE_STD(func) macro that calls
- std::func be default
- ::func when eigen is being compiled with HIPCC
This change was requested in the previous HIP PR
(https://bitbucket.org/eigen/eigen/pull-requests/518/pr-with-hip-specific-fixes-for-the-eigen/diff)
3. unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
Removing EIGEN_DEVICE_FUNC attribute from pure virtual methods as it is not supported by HIPCC
4. unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
Disabling the template specializations of InnerMostDimReducer as they run into HIPCC link errors
* Support compiling without IO streams
Add the preprocessor definition EIGEN_NO_IO which, if defined,
disables all use of the IO streams part of the standard library.
