0
0
Fork 0
mirror of https://github.com/matrix-construct/construct synced 2024-06-25 05:18:23 +02:00
construct/include/ircd/simd/transform.h

299 lines
7.3 KiB
C++

// The Construct
//
// Copyright (C) The Construct Developers, Authors & Contributors
// Copyright (C) 2016-2020 Jason Volk <jason@zemos.net>
//
// Permission to use, copy, modify, and/or distribute this software for any
// purpose with or without fee is hereby granted, provided that the above
// copyright notice and this permission notice is present in all copies. The
// full license for this software is available in the LICENSE file.
#pragma once
#define HAVE_IRCD_SIMD_TRANSFORM_H
namespace ircd::simd
{
template<class block_t>
using transform_fixed_proto = void (block_t &, block_t mask);
template<class block_t>
using transform_variable_proto = u64x2 (block_t &, block_t mask);
template<class block_t,
class lambda>
using transform_is_fixed_stride = std::is_same
<
std::invoke_result_t<lambda, block_t &, block_t>, void
>;
template<class block_t,
class lambda>
using transform_is_variable_stride = std::is_same
<
std::invoke_result_t<lambda, block_t &, block_t>, u64x2
>;
template<class block_t,
class lambda>
using transform_fixed_stride = std::enable_if
<
transform_is_fixed_stride<block_t, lambda>::value, u64x2
>;
template<class block_t,
class lambda>
using transform_variable_stride = std::enable_if
<
transform_is_variable_stride<block_t, lambda>::value, u64x2
>;
template<class block_t,
class lambda>
typename transform_fixed_stride<block_t, lambda>::type
transform(char *, const char *, const u64x2, lambda&&) noexcept;
template<class block_t,
class lambda>
typename transform_variable_stride<block_t, lambda>::type
transform(char *, const char *, const u64x2, lambda&&) noexcept;
template<class block_t,
class lambda>
pair<mutable_buffer, const_buffer>
transform(const pair<mutable_buffer, const_buffer> &, lambda&&) noexcept;
}
/// Streaming transform
///
/// Convenience wrapper using ircd::buffer. This will forward to the
/// appropriate overload. The return buffers are views on the output and input
/// buffers with a size of the respective resulting counter values. Unless
/// the closure broke the loop early the result buffers will be the same as
/// the input (contents having transformed of course).
///
template<class block_t,
class lambda>
inline std::pair<ircd::mutable_buffer, ircd::const_buffer>
ircd::simd::transform(const std::pair<mutable_buffer, const_buffer> &buf,
lambda&& closure)
noexcept
{
const auto &[output, input]
{
buf
};
const u64x2 max
{
size(output), size(input),
};
const auto res
{
transform(data(output), data(input), max, std::forward<lambda>(closure))
};
return std::pair<mutable_buffer, const_buffer>
{
{ data(output), res[0] },
{ data(input), res[1] },
};
}
/// Streaming transform
///
/// This template performs the loop boiler-plate for the developer who can
/// simply supply a conforming closure. Characteristics:
///
/// * byte-aligned (unaligned): the input and output buffers do not have to
/// be aligned and can be any size.
///
/// * full-duplex: the operation involves both input and output and there are
/// separate pointers for progress across the input and output buffers which
/// are incremented independently.
///
/// * variable-stride: progress for each iteration of the loop across the input
/// and output buffers is not fixed; the transform function may advance either
/// pointer zero to sizeof(block_t) bytes each iteration. Due to these
/// characteristics, unaligned bytes may be redundantly loaded or stored and
/// non-temporal features are not used to optimize the operation.
///
/// u64x2 counter lanes = { output_length, input_length }; The argument `max`
/// gives the buffer size in that format. The return value is the consumed
/// bytes (final counter value) in that format.
///
template<class block_t,
class lambda>
inline typename ircd::simd::transform_variable_stride<block_t, lambda>::type
ircd::simd::transform(char *const __restrict__ out,
const char *const __restrict__ in,
const u64x2 max,
lambda&& closure)
noexcept
{
using block_t_u = unaligned<block_t>;
u64x2 count
{
0, // output pos
0, // input pos
};
// primary broadband loop
while(count[1] + sizeof(block_t) <= max[1] && count[0] + sizeof(block_t) <= max[0])
{
const auto mask
{
mask_full<block_t>()
};
const auto di
{
reinterpret_cast<block_t_u *>(out + count[0])
};
const auto si
{
reinterpret_cast<const block_t_u *>(in + count[1])
};
block_t block
(
*si
);
const auto consume
{
closure(block, mask)
};
count += consume;
*di = block;
}
// trailing narrowband loop
while(count[1] < max[1])
{
block_t block {0}, mask {0};
for(size_t i(0); count[1] + i < max[1] && i < sizeof(block_t); ++i)
{
block[i] = in[count[1] + i];
mask[i] = 0xff;
}
const auto consume
{
closure(block, mask)
};
assert(consume[0] <= sizeof(block_t));
for(size_t i(0); i < consume[0] && count[0] + i < max[0]; ++i)
out[count[0] + i] = block[i];
count += consume;
}
return u64x2
{
std::min(count[0], max[0]),
std::min(count[1], max[1]),
};
}
/// Streaming transform
///
/// This template performs the loop boiler-plate for the developer who can
/// simply supply a conforming closure. Characteristics:
///
/// * byte-aligned (unaligned): the input and output buffers do not have to
/// be aligned and can be any size.
///
/// * full-duplex: the operation involves both input and output and there are
/// separate pointers for progress across the input and output buffers which
/// are incremented independently.
///
/// * fixed-stride: progress for each iteration of the loop across the input
/// and output buffers is fixed.
///
/// u64x2 counter lanes = { output_length, input_length }; The argument `max`
/// gives the buffer size in that format. The return value is the consumed
/// bytes (final counter value) in that format.
///
template<class block_t,
class lambda>
inline typename ircd::simd::transform_fixed_stride<block_t, lambda>::type
ircd::simd::transform(char *const __restrict__ out,
const char *const __restrict__ in,
const u64x2 max,
lambda&& closure)
noexcept
{
using block_t_u = unaligned<block_t>;
u64x2 count
{
0, // output pos
0, // input pos
};
// primary broadband loop
while(count[1] + sizeof(block_t) <= max[1] && count[0] + sizeof(block_t) <= max[0])
{
static const u64x2 consume
{
sizeof(block_t),
sizeof(block_t),
};
static const auto mask
{
mask_full<block_t>()
};
const auto di
{
reinterpret_cast<block_t_u *>(out + count[0])
};
const auto si
{
reinterpret_cast<const block_t_u *>(in + count[1])
};
block_t block
(
*si
);
closure(block, mask);
count += consume;
*di = block;
}
// trailing narrowband loop
assert(count[1] + sizeof(block_t) > max[1]);
if(likely(count[1] < max[1]))
{
u64 i[2] {0};
block_t block {0}, mask {0};
for(; count[1] + i[1] < max[1]; ++i[1])
{
block[i[1]] = in[count[1] + i[1]];
mask[i[1]] = 0xff;
}
closure(block, mask);
for(; i[0] < i[1] && count[0] + i[0] < max[0]; ++i[0])
out[count[0] + i[0]] = block[i[0]];
count += u64x2
{
i[0], i[1]
};
}
assert(count[0] == max[0]);
assert(count[1] == max[1]);
return count;
}