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- Move formatted printing to `hashing.cpp` instead of `hashing.h` - Separate APInt and APFloat hashing specializations into a new `hashing_llvm.h` - Update toolchain/base dependencies and include sites that hash LLVM data types to include `hashing_llvm.h` Combined, this reduces the transitive includes caused by `hashing.h`. Assisted-by: Antigravity with Gemini
1017 lines
45 KiB
C++
1017 lines
45 KiB
C++
// Part of the Carbon Language project, under the Apache License v2.0 with LLVM
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// Exceptions. See /LICENSE for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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#ifndef CARBON_COMMON_HASHING_H_
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#define CARBON_COMMON_HASHING_H_
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#include <concepts>
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#include <string>
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#include <tuple>
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#include <type_traits>
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#include <utility>
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#include "common/check.h"
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#include "common/ostream.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/ADT/StringRef.h"
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#ifdef __ARM_ACLE
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#include <arm_acle.h>
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#endif
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namespace Carbon {
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// A 64-bit hash code produced by `Carbon::HashValue`.
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//
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// This provides methods for extracting high-quality bits from the hash code
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// quickly.
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//
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// This class can also be a hashing input when recursively hashing more complex
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// data structures.
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class HashCode : public Printable<HashCode> {
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public:
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HashCode() = default;
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constexpr explicit HashCode(uint64_t value) : value_(value) {}
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friend constexpr auto operator==(HashCode lhs, HashCode rhs) -> bool {
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return lhs.value_ == rhs.value_;
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}
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friend constexpr auto operator!=(HashCode lhs, HashCode rhs) -> bool {
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return lhs.value_ != rhs.value_;
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}
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// Extracts an index from the hash code as a `ssize_t`. This index covers the
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// full range of that type, and may even be negative. Typical usage will
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// involve masking this down to some positive range using a bitand with a mask
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// computed from a power-of-two size. This routine doesn't do any masking to
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// ensure a positive index to avoid redundant computations with the typical
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// user of the index.
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constexpr auto ExtractIndex() -> ssize_t;
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// Extracts an index and a fixed `N`-bit tag from the hash code.
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//
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// This extracts these values from the position of the hash code which
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// maximizes the entropy in the tag and the low bits of the index, as typical
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// indices will be further masked down to fall in a smaller range.
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//
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// `N` must be in the range [1, 32]. The returned index will be in the range
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// [0, 2**(64-N)).
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template <int N>
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constexpr auto ExtractIndexAndTag() -> std::pair<ssize_t, uint32_t>;
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// Extract the full 64-bit hash code as an integer.
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//
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// The methods above should be preferred rather than directly manipulating
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// this integer. This is provided primarily to enable Merkle-tree hashing or
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// other recursive hashing where that is needed or more efficient.
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explicit operator uint64_t() const { return value_; }
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auto Print(llvm::raw_ostream& out) const -> void;
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private:
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uint64_t value_ = 0;
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};
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// Computes a hash code for the provided value, incorporating the provided seed.
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//
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// The seed doesn't need to be of any particular high quality, but a zero seed
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// has bad effects in several places. Prefer the unseeded routine rather than
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// providing a zero here.
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//
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// This **not** a cryptographically secure or stable hash -- it is only designed
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// for use with in-memory hash table style data structures. Being fast and
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// effective for that use case is the guiding principle of its design.
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//
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// There is no guarantee that the values produced are stable from execution to
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// execution. For speed and quality reasons, the implementation does not
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// introduce any variance to defend against accidental dependencies. As a
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// consequence, it is strongly encouraged to use a seed that varies from
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// execution to execution to avoid depending on specific values produced.
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//
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// The algorithm used is most heavily based on [Abseil's hashing algorithm][1],
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// with some additional ideas and inspiration from the fallback hashing
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// algorithm in [Rust's AHash][2] and the [FxHash][3] function. However, there
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// are also *significant* changes introduced here.
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//
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// [1]: https://github.com/abseil/abseil-cpp/tree/master/absl/hash/internal
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// [2]: https://github.com/tkaitchuck/aHash/wiki/AHash-fallback-algorithm
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// [3]: https://docs.rs/fxhash/latest/fxhash/
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//
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// This hash algorithm does *not* defend against hash flooding. While it can be
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// viewed as "keyed" on the seed, it is expected to be possible to craft inputs
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// for some data types that cancel out the seed used and manufacture endlessly
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// colliding sets of keys. In general, this function works to be *fast* for hash
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// tables. If you need to defend against hash flooding, either directly use a
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// data structure with strong worst-case guarantees, or a hash table which
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// detects catastrophic collisions and falls back to such a data structure.
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//
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// This hash function is heavily optimized for *latency* over *quality*. Modern
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// hash tables designs can efficiently handle reasonable collision rates,
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// including using extra bits from the hash to avoid all efficiency coming from
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// the same low bits. Because of this, low-latency is significantly more
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// important for performance than high-quality, and this is heavily leveraged.
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// The result is that the hash codes produced *do* have significant avalanche
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// problems for small keys. The upside is that the latency for hashing integers,
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// pointers, and small byte strings (up to 32-bytes) is exceptionally low, and
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// essentially a small constant time instruction sequence.
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//
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// No exotic instruction set extensions are required, and the state used is
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// small. It does rely on being able to get the low- and high-64-bit results of
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// a 64-bit multiply efficiently.
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//
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// The function supports many typical data types such as primitives, string-ish
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// views, and types composing primitives transparently like pairs, tuples, and
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// array-ish views. It is also extensible to support user-defined types.
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//
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// The builtin support for string-like types include:
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// - `std::string_view`
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// - `std::string`
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// - `llvm::StringRef`
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// - `llvm::SmallString`
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//
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// This function supports heterogeneous lookup between all of the string-like
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// types. It also supports heterogeneous lookup between pointer types regardless
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// of pointee type and `nullptr`.
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//
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// However, these are the only heterogeneous lookup support including for the
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// builtin in, standard, and LLVM types. Notably, each different size and
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// signedness integer type may hash differently for efficiency reasons. Hash
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// tables should pick a single integer type in which to manage keys and do
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// lookups.
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//
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// To add support for your type, you need to implement a customization point --
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// a free function that can be found by ADL for your type -- called
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// `CarbonHashValue` with the following signature:
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//
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// ```cpp
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// auto CarbonHashValue(const YourType& value, uint64_t seed) -> HashCode;
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// ```
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//
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// The extension point needs to ensure that values that compare equal (including
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// any comparisons with different types that might be used with a hash table of
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// `YourType` keys) produce the same `HashCode` values.
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//
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// `HashCode` values should typically be produced using the `Hasher` helper type
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// below. See its documentation for more details about implementing these
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// customization points and how best to incorporate the value's state into a
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// `HashCode`.
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//
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// For two input values that are almost but not quite equal, the extension
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// point should maximize the probability of each bit of their resulting
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// `HashCode`s differing. More formally, `HashCode`s should exhibit an
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// [avalanche effect][4]. However, while this is desirable, it should be
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// **secondary** to low latency. The intended use case of these functions is not
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// cryptography but in-memory hashtables where the latency and overhead of
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// computing the `HashCode` is *significantly* more important than achieving a
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// particularly high quality. The goal is to have "just enough" avalanche
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// effect, but there is not a fixed criteria for how much is enough. That should
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// be determined through practical experimentation with a hashtable and
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// distribution of keys.
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//
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// [4]: https://en.wikipedia.org/wiki/Avalanche_effect
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template <typename T>
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inline auto HashValue(const T& value, uint64_t seed) -> HashCode;
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// The same as the seeded version of `HashValue` but without callers needing to
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// provide a seed.
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//
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// Generally prefer the seeded version, but this is available if there is no
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// reasonable seed. In particular, this will behave better than using a seed of
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// `0`. One important use case is for recursive hashing of sub-objects where
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// appropriate or needed.
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template <typename T>
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inline auto HashValue(const T& value) -> HashCode;
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// Object and APIs that eventually produce a hash code.
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//
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// This type is primarily used by types to implement a customization point
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// `CarbonHashValue` that will in turn be used by the `HashValue` function. See
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// the `HashValue` function for details of that extension point.
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//
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// The methods on this type can be used to incorporate data from your
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// user-defined type into its internal state which can be converted to a
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// `HashCode` at any time. These methods will only produce the same `HashCode`
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// if they are called in the exact same order with the same arguments -- there
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// are no guaranteed equivalences between calling different methods.
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//
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// Example usage:
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// ```cpp
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// auto CarbonHashValue(const MyType& value, uint64_t seed) -> HashCode {
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// Hasher hasher(seed);
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// hasher.HashTwo(value.x, value.y);
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// return static_cast<HashCode>(hasher);
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// }
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// ```
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//
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// This type's API also reflects the reality that high-performance hash tables
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// are used with keys that are generally small and cheap to hash.
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//
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// To ensure this type's code is optimized effectively, it should typically be
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// used as a local variable and not passed across function boundaries
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// unnecessarily.
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//
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// The type also provides a number of static helper functions and static data
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// members that may be used by authors of `CarbonHashValue` implementations to
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// efficiently compute the inputs to the core `Hasher` methods, or even to
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// manually do some amounts of hashing in performance-tuned ways outside of the
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// methods provided.
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class Hasher {
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public:
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Hasher() = default;
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explicit Hasher(uint64_t seed) : buffer(seed) {}
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Hasher(Hasher&& arg) = default;
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Hasher(const Hasher& arg) = delete;
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auto operator=(Hasher&& rhs) -> Hasher& = default;
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// Extracts the current state as a `HashCode` for use.
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explicit operator HashCode() const { return HashCode(buffer); }
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// Incorporates a variable number of objects into the `hasher`s state.
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//
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// The `values` here can be anything hashable, and this routine handles
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// recursively hashing a single value as appropriate and then in turn
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// incorporating that. However, it is optimized for relatively small numbers
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// of values and/or small elements. A large tree structure will be better
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// handled by a dedicated Merkle-tree decomposition rather than the ad-hoc one
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// provided here. This routine's decomposition is mostly useful for combining
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// N small bits of data with one recursively hashed entity.
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//
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// There is no guaranteed correspondence between the behavior of a single call
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// with multiple parameters and multiple calls.
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template <typename... Ts>
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auto Hash(const Ts&... values) -> void;
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// Incorporates an array of objects into the hasher's state.
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//
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// Similar to the variadic `Hash`, this will handle recursively hashing if
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// necessary, but is optimized to avoid it when possible and is especially
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// efficient when hashing a raw array of bytes.
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//
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// Note that this is especially inefficient when it must recursively hash for
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// long arrays -- that pattern should be avoided if possible. It is usually
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// more effective to optimize that pattern at a higher level with a dedicated
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// hashing implementation.
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template <typename T>
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auto HashArray(llvm::ArrayRef<T> values) -> void;
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// Incorporates an object into the hasher's state by hashing its object
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// representation. Requires `value`'s type to have a unique object
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// representation. This is primarily useful for builtin and primitive types.
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//
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// This can be directly used for simple users combining some aggregation of
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// objects. However, when possible, prefer the variadic version below for
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// aggregating several primitive types into a hash.
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template <typename T>
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requires std::has_unique_object_representations_v<T>
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auto HashRaw(const T& value) -> void;
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// Simpler and more primitive functions to incorporate state represented in
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// `uint64_t` values into the hasher's state.
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//
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// These may be slightly less efficient than the `Hash` method above for a
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// typical application code `uint64_t`, but are designed to work well even
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// when relevant data has been packed into the `uint64_t` parameters densely.
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auto HashDense(uint64_t data) -> void;
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auto HashDense(uint64_t data0, uint64_t data1) -> void;
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// A heavily optimized routine for incorporating a dynamically sized sequence
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// of bytes into the hasher's state.
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//
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// This routine has carefully structured inline code paths for short byte
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// sequences and a reasonably high bandwidth code path for longer sequences.
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// The size of the byte sequence is always incorporated into the hasher's
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// state along with the contents.
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auto HashSizedBytes(llvm::ArrayRef<std::byte> bytes) -> void;
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// Incorporate a dynamically sized sequence of bytes represented as an array
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// of objects into the hasher's state.
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template <typename T>
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requires std::has_unique_object_representations_v<T>
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auto HashSizedBytes(llvm::ArrayRef<T> data) -> void {
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HashSizedBytes(llvm::ArrayRef<std::byte>(
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reinterpret_cast<const std::byte*>(data.data()),
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data.size() * sizeof(T)));
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}
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// An out-of-line, throughput-optimized routine for incorporating a
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// dynamically sized sequence when the sequence size is guaranteed to be >32.
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// The size is always incorporated into the state.
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auto HashSizedBytesLarge(llvm::ArrayRef<std::byte> bytes) -> void;
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// Utility functions to read data of various sizes efficiently into a
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// 64-bit value. These pointers need-not be aligned, and can alias other
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// objects. The representation of the read data in the `uint64_t` returned is
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// not stable or guaranteed.
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static auto Read1(const std::byte* data) -> uint64_t;
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static auto Read2(const std::byte* data) -> uint64_t;
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static auto Read4(const std::byte* data) -> uint64_t;
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static auto Read8(const std::byte* data) -> uint64_t;
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// Similar to the `ReadN` functions, but supports reading a range of different
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// bytes provided by the size *without branching on the size*. The lack of
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// branches is often key, and the code in these routines works to be efficient
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// in extracting a *dynamic* size of bytes into the returned `uint64_t`. There
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// may be overlap between different routines, because these routines are based
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// on different implementation techniques that do have some overlap in the
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// range of sizes they can support. Which routine is the most efficient for a
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// size in the overlap isn't trivial, and so these primitives are provided
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// as-is and should be selected based on the localized generated code and
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// benchmarked performance.
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static auto Read1To3(const std::byte* data, ssize_t size) -> uint64_t;
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static auto Read4To8(const std::byte* data, ssize_t size) -> uint64_t;
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static auto Read8To16(const std::byte* data, ssize_t size)
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-> std::pair<uint64_t, uint64_t>;
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// Reads the underlying object representation of a type into a 64-bit integer
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// efficiently. Only supports types with unique object representation and at
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// most 8-bytes large. This is typically used to read primitive types.
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template <typename T>
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requires std::has_unique_object_representations_v<T> && (sizeof(T) <= 8)
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static auto ReadSmall(const T& value) -> uint64_t;
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// The core of the hash algorithm is this mix function. The specific
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// operations are not guaranteed to be stable but are described here for
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// hashing authors to understand what to expect.
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//
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// Currently, this uses the same "mix" operation as in Abseil, AHash, and
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// several other hashing algorithms. It takes two 64-bit integers, and
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// multiplies them, capturing both the high 64-bit result and the low 64-bit
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// result, and then XOR-ing those two halves together.
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//
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// A consequence of this operation is that a zero on either side will fail to
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// incorporate any bits from the other side. Often, this is an acceptable rate
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// of collision in practice. But it is worth being aware of and working to
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// avoid common paths encountering this. For example, naively used this might
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// cause different length all-zero byte strings to hash the same, essentially
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// losing the length in the composition of the hash for a likely important
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// case of byte sequence.
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//
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// Another consequence of the particular implementation is that it is useful
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// to have a reasonable distribution of bits throughout both sides of the
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// multiplication. However, it is not *necessary* as we do capture the
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// complete 128-bit result. Where reasonable, the caller should XOR random
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// data into operands before calling `Mix` to try and increase the
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// distribution of bits feeding the multiply.
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static auto Mix(uint64_t lhs, uint64_t rhs) -> uint64_t;
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// An alternative to `Mix` that is significantly weaker but also lower
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// latency. It should not be used when the input `uint64_t` is densely packed
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// with data, but is a good option for hashing a single integer or pointer
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// where the full 64-bits are sparsely populated and especially the high bits
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// are often invariant between interestingly different values.
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//
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// This uses just the low 64-bit result of a multiply. It ensures the operand
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// is good at diffusing bits, but inherently the high bits of the input will
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// be (significantly) less often represented in the output. It also does some
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// reversal to ensure the *low* bits of the result are the most useful ones.
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static auto WeakMix(uint64_t value) -> uint64_t;
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// We have a 64-byte random data pool designed to fit on a single cache line.
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// This routine allows sampling it at byte indices, which allows getting 64 -
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// 8 different random 64-bit results. The offset must be in the range [0, 56).
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static auto SampleRandomData(ssize_t offset) -> uint64_t {
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CARBON_DCHECK(offset + sizeof(uint64_t) < sizeof(StaticRandomData));
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uint64_t data;
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memcpy(&data,
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reinterpret_cast<const unsigned char*>(&StaticRandomData) + offset,
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sizeof(data));
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return data;
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}
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// As above, but for small offsets, we can use aligned loads, which are
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// faster. The offset must be in the range [0, 8).
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static auto SampleAlignedRandomData(ssize_t offset) -> uint64_t {
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CARBON_DCHECK(static_cast<size_t>(offset) <
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sizeof(StaticRandomData) / sizeof(uint64_t));
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return StaticRandomData[offset];
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}
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// Random data taken from the hexadecimal digits of Pi's fractional component,
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// written in lexical order for convenience of reading. The resulting
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// byte-stream will be different due to little-endian integers. These can be
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// used directly for convenience rather than calling `SampleRandomData`, but
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// be aware that this is the underlying pool. The goal is to reuse the same
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// single cache-line of constant data.
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//
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// The initializers here can be generated with the following shell script,
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// which will generate 8 64-bit values and one more digit. The `bc` command's
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// decimal based scaling means that without getting at least some extra hex
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// digits rendered there will be rounding that we don't want so the script
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// below goes on to produce one more hex digit ensuring the 8 initializers
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// aren't rounded in any way. Using a higher scale won't cause the 8
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// initializers here to change further.
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//
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// ```sh
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// echo 'obase=16; scale=155; 4*a(1)' | env BC_LINE_LENGTH=500 bc -l \
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// | cut -c 3- | tr '[:upper:]' '[:lower:]' \
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// | sed -e "s/.\{4\}/&'/g" \
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// | sed -e "s/\(.\{4\}'.\{4\}'.\{4\}'.\{4\}\)'/0x\1,\n/g"
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// ```
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alignas(64) static constexpr std::array<uint64_t, 8> StaticRandomData = {
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0x243f'6a88'85a3'08d3, 0x1319'8a2e'0370'7344, 0xa409'3822'299f'31d0,
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0x082e'fa98'ec4e'6c89, 0x4528'21e6'38d0'1377, 0xbe54'66cf'34e9'0c6c,
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0xc0ac'29b7'c97c'50dd, 0x3f84'd5b5'b547'0917,
|
|
};
|
|
|
|
// We need a multiplicative hashing constant for both 64-bit multiplicative
|
|
// hashing fast paths and some other 128-bit folded multiplies. We use an
|
|
// empirically better constant compared to Knuth's, Rust's FxHash, and others
|
|
// we've tried. It was found by a search of uniformly distributed odd numbers
|
|
// and examining them for desirable properties when used as a multiplicative
|
|
// hash, however our search seems largely to have been lucky rather than
|
|
// having a highly effective set of criteria. We evaluated this constant by
|
|
// integrating this hash function with a hashtable and looking at the
|
|
// collision rates of several different but very fundamental patterns of keys:
|
|
// integers counting from 0, pointers allocated on the heap, and strings with
|
|
// character and size distributions matching C-style ASCII identifiers.
|
|
// Different constants found with this search worked better or less well, but
|
|
// fairly consistently across the different types of keys. At the end, far and
|
|
// away the best behaved constant we found was one of the first ones in the
|
|
// search and is what we use here.
|
|
//
|
|
// For reference, some other constants include one derived by diving 2^64 by
|
|
// Phi: 0x9e37'79b9'7f4a'7c15U -- see these sites for details:
|
|
// https://probablydance.com/2018/06/16/fibonacci-hashing-the-optimization-that-the-world-forgot-or-a-better-alternative-to-integer-modulo/
|
|
// https://book.huihoo.com/data-structures-and-algorithms-with-object-oriented-design-patterns-in-c++/html/page214.html
|
|
//
|
|
// Another very good constant derived by minimizing repeating bit patterns is
|
|
// 0xdcb2'2ca6'8cb1'34edU and its bit-reversed form. However, this constant
|
|
// has observed frequent issues at roughly 4k pointer keys, connected to a
|
|
// common hashtable seed also being a pointer. These issues appear to occur
|
|
// both more often and have a larger impact relative to the number of keys
|
|
// than the rare cases where some combinations of pointer seeds and pointer
|
|
// keys create minor quality issues with the constant we use.
|
|
static constexpr uint64_t MulConstant = 0x79d5'f9e0'de1e'8cf5U;
|
|
|
|
private:
|
|
uint64_t buffer;
|
|
};
|
|
|
|
// A dedicated namespace for `CarbonHashValue` overloads that are not found by
|
|
// ADL with their associated types. For example, primitive type overloads or
|
|
// overloads for types in LLVM's libraries.
|
|
//
|
|
// Note that these are internal implementation details and **not** part of the
|
|
// public API. They should not be used directly by client code.
|
|
namespace InternalHashDispatch {
|
|
|
|
template <typename T>
|
|
inline auto CarbonHashValue(llvm::ArrayRef<T> values, uint64_t seed)
|
|
-> HashCode {
|
|
Hasher hasher(seed);
|
|
hasher.HashArray(values);
|
|
return static_cast<HashCode>(hasher);
|
|
}
|
|
|
|
inline auto CarbonHashValue(llvm::ArrayRef<std::byte> bytes, uint64_t seed)
|
|
-> HashCode {
|
|
Hasher hasher(seed);
|
|
hasher.HashSizedBytes(bytes);
|
|
return static_cast<HashCode>(hasher);
|
|
}
|
|
|
|
// Hashing implementation for `llvm::StringRef`. We forward all the other
|
|
// string-like types that support heterogeneous lookup to this one.
|
|
inline auto CarbonHashValue(llvm::StringRef value, uint64_t seed) -> HashCode {
|
|
return CarbonHashValue(
|
|
llvm::ArrayRef(reinterpret_cast<const std::byte*>(value.data()),
|
|
value.size()),
|
|
seed);
|
|
}
|
|
|
|
inline auto CarbonHashValue(std::string_view value, uint64_t seed) -> HashCode {
|
|
return CarbonHashValue(llvm::StringRef(value.data(), value.size()), seed);
|
|
}
|
|
|
|
inline auto CarbonHashValue(const std::string& value, uint64_t seed)
|
|
-> HashCode {
|
|
return CarbonHashValue(llvm::StringRef(value.data(), value.size()), seed);
|
|
}
|
|
|
|
template <unsigned Length>
|
|
inline auto CarbonHashValue(const llvm::SmallString<Length>& value,
|
|
uint64_t seed) -> HashCode {
|
|
return CarbonHashValue(llvm::StringRef(value.data(), value.size()), seed);
|
|
}
|
|
|
|
// Support types that are array-like by building an `llvm::ArrayRef` out of
|
|
// them. We can't do this by accepting any type convertible to an `ArrayRef`
|
|
// because that type supports building a synthetic array out of any single
|
|
// element.
|
|
template <typename T>
|
|
inline auto CarbonHashValue(const std::vector<T>& arg, uint64_t seed)
|
|
-> HashCode {
|
|
return CarbonHashValue(llvm::ArrayRef(arg), seed);
|
|
}
|
|
template <typename T>
|
|
inline auto CarbonHashValue(const llvm::SmallVectorImpl<T>& arg, uint64_t seed)
|
|
-> HashCode {
|
|
return CarbonHashValue(llvm::ArrayRef(arg), seed);
|
|
}
|
|
template <typename T, size_t N>
|
|
inline auto CarbonHashValue(const std::array<T, N>& arg, uint64_t seed)
|
|
-> HashCode {
|
|
return CarbonHashValue(llvm::ArrayRef(arg), seed);
|
|
}
|
|
template <typename T, size_t N>
|
|
inline auto CarbonHashValue(const T (&arg)[N], uint64_t seed) -> HashCode {
|
|
return CarbonHashValue(llvm::ArrayRef(arg), seed);
|
|
}
|
|
|
|
template <typename... Ts>
|
|
inline auto CarbonHashValue(const std::tuple<Ts...>& value, uint64_t seed)
|
|
-> HashCode {
|
|
Hasher hasher(seed);
|
|
std::apply([&](const auto&... args) { hasher.Hash(args...); }, value);
|
|
return static_cast<HashCode>(hasher);
|
|
}
|
|
|
|
template <typename T, typename U>
|
|
inline auto CarbonHashValue(const std::pair<T, U>& value, uint64_t seed)
|
|
-> HashCode {
|
|
Hasher hasher(seed);
|
|
hasher.Hash(value.first, value.second);
|
|
return static_cast<HashCode>(hasher);
|
|
}
|
|
|
|
// Extension point for types defined outside of Carbon that cannot be found by
|
|
// ADL in their own namespace and cannot be declared before this point.
|
|
template <typename T>
|
|
struct CustomHashValue;
|
|
|
|
template <typename T>
|
|
concept HasCustomHashValue = requires { CustomHashValue<T>::Hash; };
|
|
|
|
// Implementation detail predicate to detect if there is a `CarbonHashValue`
|
|
// overload available for a particular type, either in this namespace or found
|
|
// via ADL. Note that this should not be moved above any overloads.
|
|
template <typename T>
|
|
concept HasCarbonHashValue = requires(const T& value, uint64_t seed) {
|
|
{ CarbonHashValue(value, seed) } -> std::same_as<HashCode>;
|
|
};
|
|
|
|
// C++ guarantees this is true for the unsigned variants, but we require it for
|
|
// signed variants and pointers.
|
|
static_assert(std::has_unique_object_representations_v<int8_t>);
|
|
static_assert(std::has_unique_object_representations_v<int16_t>);
|
|
static_assert(std::has_unique_object_representations_v<int32_t>);
|
|
static_assert(std::has_unique_object_representations_v<int64_t>);
|
|
static_assert(std::has_unique_object_representations_v<void*>);
|
|
|
|
// Overloaded function to provide mappings or conversions required to types that
|
|
// should be hashed as plain data but where can't directly examine the storage.
|
|
//
|
|
// For example, C++ uses `std::nullptr_t` but unfortunately doesn't make it have
|
|
// a unique object representation. To address that, we need a function that
|
|
// converts `nullptr` back into a `void*` that will have a unique object
|
|
// representation. And this needs to be done by-value as we need to build a
|
|
// temporary object to return, which requires a separate overload rather than
|
|
// just using a type function that could be used in parallel in the predicate
|
|
// below. Instead, we build the predicate independently of the mapping overload,
|
|
// but together they should produce the correct result.
|
|
template <typename T>
|
|
inline auto MapToRawDataType(const T& value) -> const T& {
|
|
// This overload should never be selected for `std::nullptr_t`, so
|
|
// static_assert to get some better compiler error messages.
|
|
static_assert(!std::same_as<T, std::nullptr_t>);
|
|
// NOLINTNEXTLINE(bugprone-return-const-ref-from-parameter)
|
|
return value;
|
|
}
|
|
inline auto MapToRawDataType(std::nullptr_t /*value*/) -> const void* {
|
|
return nullptr;
|
|
}
|
|
|
|
// Implementation detail predicate to detect if we can hash as a raw data type.
|
|
// When used, it should be combined with our mapping function `MapToRawDataType`
|
|
// to handle any necessary edge cases that don't directly work.
|
|
template <typename T>
|
|
concept CanHashAsRawDataType = std::same_as<T, std::nullptr_t> ||
|
|
std::has_unique_object_representations_v<T>;
|
|
|
|
// Implementation of the unqualified dispatch to any provided `CarbonHashValue`
|
|
// overloads, either here, or via ADL. Note that similar to
|
|
// `HasCarbonHashValue`, this must not be moved above any of those overloads.
|
|
template <typename T>
|
|
inline auto DispatchImpl(const T& value, uint64_t seed) -> HashCode {
|
|
if constexpr (HasCarbonHashValue<T>) {
|
|
// If we have an explicit overload for `CarbonHashValue`, call it. This may
|
|
// be provided above or via ADL, and is preferred as it represents an
|
|
// explicit request for how the type is hashed.
|
|
return CarbonHashValue(value, seed);
|
|
} else if constexpr (HasCustomHashValue<T>) {
|
|
// If we have an explicit specialization for `CustomHashValue`, call it.
|
|
// This is a fallback explicit hashing path that doesn't require ADL or
|
|
// being in this header.
|
|
return CustomHashValue<T>::Hash(value, seed);
|
|
} else if constexpr (CanHashAsRawDataType<T>) {
|
|
// There was no explicit overload or specialization to call, but the type
|
|
// allows us to hash it as raw data, do so.
|
|
Hasher hasher(seed);
|
|
hasher.HashRaw(MapToRawDataType(value));
|
|
return static_cast<HashCode>(hasher);
|
|
} else {
|
|
// We can only synthesize hashing for types that are hashable as raw data.
|
|
// This type isn't so fail a static assert due to the lack of an overload.
|
|
// We use the concept here to try and get the best diagnostics we can about
|
|
// candidates.
|
|
static_assert(HasCarbonHashValue<T>,
|
|
"Attempted to hash a type which does not have a "
|
|
"`CarbonHashValue` overload.");
|
|
}
|
|
}
|
|
|
|
} // namespace InternalHashDispatch
|
|
|
|
template <typename T>
|
|
inline auto HashValue(const T& value, uint64_t seed) -> HashCode {
|
|
return InternalHashDispatch::DispatchImpl(value, seed);
|
|
}
|
|
|
|
template <typename T>
|
|
inline auto HashValue(const T& value) -> HashCode {
|
|
// When a seed isn't provided, use the last 64-bit chunk of random data. Other
|
|
// chunks (especially the first) are more often XOR-ed with the seed and risk
|
|
// cancelling each other out and feeding a zero to a `Mix` call in a way that
|
|
// sharply increasing collisions.
|
|
return HashValue(value, Hasher::StaticRandomData[7]);
|
|
}
|
|
|
|
constexpr auto HashCode::ExtractIndex() -> ssize_t { return value_; }
|
|
|
|
template <int N>
|
|
constexpr auto HashCode::ExtractIndexAndTag() -> std::pair<ssize_t, uint32_t> {
|
|
static_assert(N >= 1);
|
|
static_assert(N < 32);
|
|
return {static_cast<ssize_t>(value_ >> N),
|
|
static_cast<uint32_t>(value_ & ((1U << N) - 1))};
|
|
}
|
|
|
|
// Building with `-DCARBON_MCA_MARKERS` will enable `llvm-mca` annotations in
|
|
// the source code. These can interfere with optimization, but allows analyzing
|
|
// the generated `.s` file with the `llvm-mca` tool. Documentation for these
|
|
// markers is here:
|
|
// https://llvm.org/docs/CommandGuide/llvm-mca.html#using-markers-to-analyze-specific-code-blocks
|
|
#if CARBON_MCA_MARKERS
|
|
#define CARBON_MCA_BEGIN(NAME) \
|
|
__asm volatile("# LLVM-MCA-BEGIN " NAME "" ::: "memory");
|
|
#define CARBON_MCA_END(NAME) \
|
|
__asm volatile("# LLVM-MCA-END " NAME "" ::: "memory");
|
|
#else
|
|
#define CARBON_MCA_BEGIN(NAME)
|
|
#define CARBON_MCA_END(NAME)
|
|
#endif
|
|
|
|
inline auto Hasher::Read1(const std::byte* data) -> uint64_t {
|
|
uint8_t result;
|
|
std::memcpy(&result, data, sizeof(result));
|
|
return result;
|
|
}
|
|
|
|
inline auto Hasher::Read2(const std::byte* data) -> uint64_t {
|
|
uint16_t result;
|
|
std::memcpy(&result, data, sizeof(result));
|
|
return result;
|
|
}
|
|
|
|
inline auto Hasher::Read4(const std::byte* data) -> uint64_t {
|
|
uint32_t result;
|
|
std::memcpy(&result, data, sizeof(result));
|
|
return result;
|
|
}
|
|
|
|
inline auto Hasher::Read8(const std::byte* data) -> uint64_t {
|
|
uint64_t result;
|
|
std::memcpy(&result, data, sizeof(result));
|
|
return result;
|
|
}
|
|
|
|
inline auto Hasher::Read1To3(const std::byte* data, ssize_t size) -> uint64_t {
|
|
// Use carefully crafted indexing to avoid branches on the exact size while
|
|
// reading.
|
|
uint64_t byte0 = static_cast<uint8_t>(data[0]);
|
|
uint64_t byte1 = static_cast<uint8_t>(data[size - 1]);
|
|
uint64_t byte2 = static_cast<uint8_t>(data[size >> 1]);
|
|
return (byte0 << 8) | (byte1 << 16) | byte2;
|
|
}
|
|
|
|
inline auto Hasher::Read4To8(const std::byte* data, ssize_t size) -> uint64_t {
|
|
uint32_t low;
|
|
std::memcpy(&low, data, sizeof(low));
|
|
uint32_t high;
|
|
std::memcpy(&high, data + size - sizeof(high), sizeof(high));
|
|
return (static_cast<uint64_t>(low) << 32) | high;
|
|
}
|
|
|
|
inline auto Hasher::Read8To16(const std::byte* data, ssize_t size)
|
|
-> std::pair<uint64_t, uint64_t> {
|
|
uint64_t low;
|
|
std::memcpy(&low, data, sizeof(low));
|
|
uint64_t high;
|
|
std::memcpy(&high, data + size - sizeof(high), sizeof(high));
|
|
return {low, high};
|
|
}
|
|
|
|
inline auto Hasher::Mix(uint64_t lhs, uint64_t rhs) -> uint64_t {
|
|
// Use the C23 extended integer support that Clang provides as a general
|
|
// language extension.
|
|
using U128 = unsigned _BitInt(128);
|
|
U128 result = static_cast<U128>(lhs) * static_cast<U128>(rhs);
|
|
return static_cast<uint64_t>(result) ^ static_cast<uint64_t>(result >> 64);
|
|
}
|
|
|
|
inline auto Hasher::WeakMix(uint64_t value) -> uint64_t {
|
|
value *= MulConstant;
|
|
#ifdef __ARM_ACLE
|
|
// Arm has a fast bit-reversal that gives us the optimal distribution.
|
|
value = __rbitll(value);
|
|
#else
|
|
// Otherwise, assume an optimized BSWAP such as x86's. That's close enough.
|
|
value = __builtin_bswap64(value);
|
|
#endif
|
|
return value;
|
|
}
|
|
|
|
inline auto Hasher::HashDense(uint64_t data) -> void {
|
|
// When hashing exactly one 64-bit entity use the Phi-derived constant as this
|
|
// is just multiplicative hashing. The initial buffer is mixed on input to
|
|
// pipeline with materializing the constant.
|
|
buffer = Mix(data ^ buffer, MulConstant);
|
|
}
|
|
|
|
inline auto Hasher::HashDense(uint64_t data0, uint64_t data1) -> void {
|
|
// When hashing two chunks of data at the same time, we XOR it with random
|
|
// data to avoid common inputs from having especially bad multiplicative
|
|
// effects. We also XOR in the starting buffer as seed or to chain. Note that
|
|
// we don't use *consecutive* random data 64-bit values to avoid a common
|
|
// compiler "optimization" of loading both 64-bit chunks into a 128-bit vector
|
|
// and doing the XOR in the vector unit. The latency of extracting the data
|
|
// afterward eclipses any benefit. Callers will routinely have two consecutive
|
|
// data values here, but using non-consecutive keys avoids any vectorization
|
|
// being tempting.
|
|
//
|
|
// XOR-ing both the incoming state and a random word over the second data is
|
|
// done to pipeline with materializing the constants and is observed to have
|
|
// better performance than XOR-ing after the mix.
|
|
//
|
|
// This roughly matches the mix pattern used in the larger mixing routines
|
|
// from Abseil, which is a more minimal form than used in other algorithms
|
|
// such as AHash and seems adequate for latency-optimized use cases.
|
|
buffer =
|
|
Mix(data0 ^ StaticRandomData[1], data1 ^ StaticRandomData[3] ^ buffer);
|
|
}
|
|
|
|
template <typename T>
|
|
requires std::has_unique_object_representations_v<T> && (sizeof(T) <= 8)
|
|
inline auto Hasher::ReadSmall(const T& value) -> uint64_t {
|
|
const auto* storage = reinterpret_cast<const std::byte*>(&value);
|
|
if constexpr (sizeof(T) == 1) {
|
|
return Read1(storage);
|
|
} else if constexpr (sizeof(T) == 2) {
|
|
return Read2(storage);
|
|
} else if constexpr (sizeof(T) == 3) {
|
|
return Read2(storage) | (Read1(&storage[2]) << 16);
|
|
} else if constexpr (sizeof(T) == 4) {
|
|
return Read4(storage);
|
|
} else if constexpr (sizeof(T) == 5) {
|
|
return Read4(storage) | (Read1(&storage[4]) << 32);
|
|
} else if constexpr (sizeof(T) == 6 || sizeof(T) == 7) {
|
|
// Use overlapping 4-byte reads for 6 and 7 bytes.
|
|
return Read4(storage) | (Read4(&storage[sizeof(T) - 4]) << 32);
|
|
} else if constexpr (sizeof(T) == 8) {
|
|
return Read8(storage);
|
|
} else {
|
|
static_assert(sizeof(T) <= 8);
|
|
}
|
|
}
|
|
|
|
template <typename... Ts>
|
|
inline auto Hasher::Hash(const Ts&... values) -> void {
|
|
if constexpr (sizeof...(Ts) == 0) {
|
|
buffer ^= StaticRandomData[0];
|
|
return;
|
|
}
|
|
|
|
using InternalHashDispatch::CanHashAsRawDataType;
|
|
using InternalHashDispatch::HasCarbonHashValue;
|
|
using InternalHashDispatch::HasCustomHashValue;
|
|
using InternalHashDispatch::MapToRawDataType;
|
|
|
|
// Special-case a single element tuple that we will hash as raw data.
|
|
if constexpr (sizeof...(Ts) == 1 &&
|
|
(... && (!HasCarbonHashValue<Ts> && !HasCustomHashValue<Ts> &&
|
|
CanHashAsRawDataType<Ts>))) {
|
|
HashRaw(MapToRawDataType(values)...);
|
|
return;
|
|
}
|
|
|
|
// Map each value into a uint64_t, either by hashing it using any custom hash
|
|
// function required, reading its data into a 64-bit value, or if large
|
|
// hashing it as raw data and using that hash code as the 64-bit data. This
|
|
// mirrors the logic in `InternalHashDispatch::DispatchImpl`, but minimizes
|
|
// early hashing of anything small we can just read as data. While this may be
|
|
// a little bit wasteful in some cases, collapsing down to a flat array of
|
|
// 64-bit integers is more efficient to hash.
|
|
auto map_value = []<typename T>(const T& value) -> uint64_t {
|
|
if constexpr (HasCarbonHashValue<T> || HasCustomHashValue<T>) {
|
|
// Use the top-level `HashValue` to re-dispatch to the custom
|
|
// implementation with a fixed seed.
|
|
return static_cast<uint64_t>(HashValue(value));
|
|
} else if constexpr (CanHashAsRawDataType<T>) {
|
|
auto raw_value = MapToRawDataType(value);
|
|
if constexpr (sizeof(raw_value) <= 8) {
|
|
return ReadSmall(raw_value);
|
|
} else {
|
|
// Use the top-level `HashValue` to pick up a good fixed seed and hash
|
|
// this large object as raw data.
|
|
return static_cast<uint64_t>(HashValue(raw_value));
|
|
}
|
|
} else {
|
|
// We can only synthesize hashing for types that are hashable as raw data.
|
|
// This type isn't so fail a static assert due to the lack of an overload.
|
|
// We use the concept here to try and get the best diagnostics we can
|
|
// about candidates.
|
|
static_assert(HasCarbonHashValue<T>,
|
|
"Attempted to hash a type which does not have a "
|
|
"`CarbonHashValue` overload.");
|
|
}
|
|
};
|
|
const uint64_t data[] = {map_value(values)...};
|
|
if constexpr (sizeof...(Ts) == 2) {
|
|
HashDense(data[0], data[1]);
|
|
return;
|
|
}
|
|
|
|
HashRaw(data);
|
|
}
|
|
|
|
template <typename T>
|
|
inline auto Hasher::HashArray(llvm::ArrayRef<T> values) -> void {
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using InternalHashDispatch::CanHashAsRawDataType;
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using InternalHashDispatch::HasCarbonHashValue;
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using InternalHashDispatch::HasCustomHashValue;
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// This logic similarly mirrors `InternalHashDispatch::DispatchImpl`, but is
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// specialized here to allow us to efficiently process the array when it
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// *doesn't* require recursive hashing.
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if constexpr (HasCarbonHashValue<T> || HasCustomHashValue<T>) {
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// Use a trivial loop to give consistent behavior for arrays requiring
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// recursive hashing. This isn't terribly efficient, but if clients care
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// they should specialize the entire hashing operation. For simple, tiny
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// cases, this avoids an awkward functionality cliff.
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for (const T& value : values) {
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HashDense(static_cast<uint64_t>(HashValue(value)));
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}
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HashRaw(values.size());
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} else if constexpr (std::has_unique_object_representations_v<T>) {
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// This code is a narrow special case for `CanHashAsRawDataType` that we can
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// further hash the underlying storage directly. We check that it is a
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// subset.
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static_assert(CanHashAsRawDataType<T>);
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HashSizedBytes(values);
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} else {
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// We can only synthesize hashing for types that are hashable as raw data.
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// This type isn't so fail a static assert due to the lack of an overload.
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// We use the concept here to try and get the best diagnostics we can
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// about candidates.
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static_assert(HasCarbonHashValue<T>,
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"Attempted to hash a type which does not have a "
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"`CarbonHashValue` overload.");
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}
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}
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template <typename T>
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requires std::has_unique_object_representations_v<T>
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inline auto Hasher::HashRaw(const T& value) -> void {
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if constexpr (sizeof(T) <= 8) {
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// For types size 8-bytes and smaller directly being hashed (as opposed to
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// 8-bytes potentially bit-packed with data), we rarely expect the incoming
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// data to fully and densely populate all 8 bytes. For these cases we have a
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// `WeakMix` routine that is lower latency but lower quality.
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CARBON_MCA_BEGIN("fixed-8b");
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buffer = WeakMix(buffer ^ ReadSmall(value));
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CARBON_MCA_END("fixed-8b");
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return;
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}
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const auto* data_ptr = reinterpret_cast<const std::byte*>(&value);
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if constexpr (8 < sizeof(T) && sizeof(T) <= 16) {
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CARBON_MCA_BEGIN("fixed-16b");
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auto values = Read8To16(data_ptr, sizeof(T));
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HashDense(values.first, values.second);
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CARBON_MCA_END("fixed-16b");
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return;
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}
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if constexpr (16 < sizeof(T) && sizeof(T) <= 32) {
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CARBON_MCA_BEGIN("fixed-32b");
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// Essentially the same technique used for dynamically sized byte sequences
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// of this size, but we start with a fixed XOR of random data.
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buffer ^= StaticRandomData[0];
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uint64_t m0 = Mix(Read8(data_ptr) ^ StaticRandomData[1],
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Read8(data_ptr + 8) ^ buffer);
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const std::byte* tail_16b_ptr = data_ptr + (sizeof(T) - 16);
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uint64_t m1 = Mix(Read8(tail_16b_ptr) ^ StaticRandomData[3],
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Read8(tail_16b_ptr + 8) ^ buffer);
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buffer = m0 ^ m1;
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CARBON_MCA_END("fixed-32b");
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return;
|
|
}
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|
|
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// Hashing the size isn't relevant here, but is harmless, so fall back to a
|
|
// common code path.
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HashSizedBytesLarge(llvm::ArrayRef<std::byte>(data_ptr, sizeof(T)));
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|
}
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|
|
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inline auto Hasher::HashSizedBytes(llvm::ArrayRef<std::byte> bytes) -> void {
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const std::byte* data_ptr = bytes.data();
|
|
const ssize_t size = bytes.size();
|
|
|
|
// First handle short sequences under 8 bytes. We distribute the branches a
|
|
// bit for short strings.
|
|
if (size <= 8) {
|
|
if (size >= 4) {
|
|
CARBON_MCA_BEGIN("dynamic-8b");
|
|
uint64_t data = Read4To8(data_ptr, size);
|
|
// We optimize for latency on short strings by hashing both the data and
|
|
// size in a single multiply here, using the small nature of size to
|
|
// sample a specific sequence of bytes with well distributed bits into one
|
|
// side of the multiply. This results in a *statistically* weak hash
|
|
// function, but one with very low latency.
|
|
//
|
|
// Note that we don't drop to the `WeakMix` routine here because we want
|
|
// to use sampled random data to encode the size, which may not be as
|
|
// effective without the full 128-bit folded result.
|
|
buffer = Mix(data ^ buffer, SampleAlignedRandomData(size - 1));
|
|
CARBON_MCA_END("dynamic-8b");
|
|
return;
|
|
}
|
|
|
|
// When we only have 0-3 bytes of string, we can avoid the cost of `Mix`.
|
|
// Instead, for empty strings we can just XOR some of our data against the
|
|
// existing buffer. For 1-3 byte lengths we do 3 one-byte reads adjusted to
|
|
// always read in-bounds without branching. Then we OR the size into the 4th
|
|
// byte and use `WeakMix`.
|
|
CARBON_MCA_BEGIN("dynamic-4b");
|
|
if (size == 0) {
|
|
buffer ^= StaticRandomData[0];
|
|
} else {
|
|
uint64_t data = Read1To3(data_ptr, size) | size << 24;
|
|
buffer = WeakMix(data);
|
|
}
|
|
CARBON_MCA_END("dynamic-4b");
|
|
return;
|
|
}
|
|
|
|
if (size <= 16) {
|
|
CARBON_MCA_BEGIN("dynamic-16b");
|
|
// Similar to the above, we optimize primarily for latency here and spread
|
|
// the incoming data across both ends of the multiply. Note that this does
|
|
// have a drawback -- any time one half of the mix function becomes zero it
|
|
// will fail to incorporate any bits from the other half. However, there is
|
|
// exactly 1 in 2^64 values for each side that achieve this, and only when
|
|
// the size is exactly 16 -- for smaller sizes there is an overlapping byte
|
|
// that makes this impossible unless the seed is *also* incredibly unlucky.
|
|
//
|
|
// Because this hash function makes no attempt to defend against hash
|
|
// flooding, we accept this risk in order to keep the latency low. If this
|
|
// becomes a non-flooding problem, we can restrict the size to <16 and send
|
|
// the 16-byte case down the next tier of cost.
|
|
uint64_t size_hash = SampleRandomData(size);
|
|
auto data = Read8To16(data_ptr, size);
|
|
buffer = Mix(data.first ^ size_hash, data.second ^ buffer);
|
|
CARBON_MCA_END("dynamic-16b");
|
|
return;
|
|
}
|
|
|
|
if (size <= 32) {
|
|
CARBON_MCA_BEGIN("dynamic-32b");
|
|
// Do two mixes of overlapping 16-byte ranges in parallel to minimize
|
|
// latency. We also incorporate the size by sampling random data into the
|
|
// seed before both.
|
|
buffer ^= SampleRandomData(size);
|
|
uint64_t m0 = Mix(Read8(data_ptr) ^ StaticRandomData[1],
|
|
Read8(data_ptr + 8) ^ buffer);
|
|
|
|
const std::byte* tail_16b_ptr = data_ptr + (size - 16);
|
|
uint64_t m1 = Mix(Read8(tail_16b_ptr) ^ StaticRandomData[3],
|
|
Read8(tail_16b_ptr + 8) ^ buffer);
|
|
// Just an XOR mix at the end is quite weak here, but we prefer that for
|
|
// latency over a more robust approach. Doing another mix with the size (the
|
|
// way longer string hashing does) increases the latency on x86-64
|
|
// significantly (approx. 20%).
|
|
buffer = m0 ^ m1;
|
|
CARBON_MCA_END("dynamic-32b");
|
|
return;
|
|
}
|
|
|
|
HashSizedBytesLarge(bytes);
|
|
}
|
|
|
|
} // namespace Carbon
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#endif // CARBON_COMMON_HASHING_H_
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