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-rw-r--r--absl/hash/internal/hash.h20
1 files changed, 17 insertions, 3 deletions
diff --git a/absl/hash/internal/hash.h b/absl/hash/internal/hash.h
index dbdc2050..ccf4cc1a 100644
--- a/absl/hash/internal/hash.h
+++ b/absl/hash/internal/hash.h
@@ -49,6 +49,7 @@
#include "absl/hash/internal/city.h"
#include "absl/hash/internal/low_level_hash.h"
#include "absl/meta/type_traits.h"
+#include "absl/numeric/bits.h"
#include "absl/numeric/int128.h"
#include "absl/strings/string_view.h"
#include "absl/types/optional.h"
@@ -1052,7 +1053,7 @@ class ABSL_DLL MixingHashState : public HashStateBase<MixingHashState> {
uint64_t most_significant = low_mem;
uint64_t least_significant = high_mem;
#endif
- return {least_significant, most_significant >> (128 - len * 8)};
+ return {least_significant, most_significant};
}
// Reads 4 to 8 bytes from p. Zero pads to fill uint64_t.
@@ -1183,9 +1184,22 @@ inline uint64_t MixingHashState::CombineContiguousImpl(
}
v = Hash64(first, len);
} else if (len > 8) {
+ // This hash function was constructed by the ML-driven algorithm discovery
+ // using reinforcement learning. We fed the agent lots of inputs from
+ // microbenchmarks, SMHasher, low hamming distance from generated inputs and
+ // picked up the one that was good on micro and macrobenchmarks.
auto p = Read9To16(first, len);
- state = Mix(state, p.first);
- v = p.second;
+ uint64_t lo = p.first;
+ uint64_t hi = p.second;
+ // Rotation by 53 was found to be most often useful when discovering these
+ // hashing algorithms with ML techniques.
+ lo = absl::rotr(lo, 53);
+ state += kMul;
+ lo += state;
+ state ^= hi;
+ uint128 m = state;
+ m *= lo;
+ return static_cast<uint64_t>(m ^ (m >> 64));
} else if (len >= 4) {
v = Read4To8(first, len);
} else if (len > 0) {