Making them trivially copyable allows using std::memcpy() without undefined
behaviors.
Only Matrix and Array with trivially copyable DenseStorage are marked as
trivially copyable with an additional type trait.
As described in http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2019/p0848r3.html
it requires extremely verbose SFINAE to make the special member functions of
fixed-size Matrix and Array trivial, unless C++20 concepts are available to
simplify the selection of trivial special member functions given template
parameters. Therefore only make this feature available to compilers that support
C++20 P0848R3.
Fix#1855.
- The current implementation computes `size + total_threads`, which can
overflow and cause CUDA_ERROR_ILLEGAL_ADDRESS when size is close to
the maximum representable value.
- The num_blocks calculation can also overflow due to the implementation
of divup().
- This patch prevents these overflows and allows the kernel to work
correctly for the full representable range of tensor sizes.
- Also adds relevant tests.
For some reason, having `take<n, numeric_list<T>>` for `n > 0` causes
g++-11 to ICE with
```
sorry, unimplemented: unexpected AST of kind nontype_argument_pack
```
It does work with other versions of gcc, and with clang.
I filed a GCC bug
[here](https://gcc.gnu.org/bugzilla/show_bug.cgi?id=102999).
Technically we should never actually run into this case, since you
can't take n > 0 elements from an empty list. Commenting it out
allows our Eigen tests to pass.
The sum accuracy test currently uses the default test precision for
the given scalar type. However, scalars are generated via a normal
distribution, and given a large enough count and strong enough random
generator, the expected sum is zero. This causes the test to
periodically fail.
Here we estimate an upper-bound for the error as `sqrt(N) * prec` for
summing N values, with each having an approximate epsilon of `prec`.
Also fixed a few warnings generated by MSVC when compiling the
reduction test.
