Result for 9663AC09BC9D2EAE62C2300DAD4135CB6229A2CA

Query result

Key Value
FileName./usr/lib64/ghc-8.10.7/splitmix-0.1.0.4/libHSsplitmix-0.1.0.4-2Vk17ilFpJOHvYIcBN29Ar-ghc8.10.7.so
FileSize113648
MD58F98B591AC490D4DDEF520F52189B6CA
SHA-19663AC09BC9D2EAE62C2300DAD4135CB6229A2CA
SHA-2568736DC880038463662327BF6DB451265FE580AAEE7F81EE0BEF171037E8B570D
SSDEEP768:jmdxGJOjN/o5msu4O+xTsrS17xLfuoJre8Aq4NbgzEE+Sw3Ad/boqKy6BvrfTkQd:jmdxGINo5fu4JsrS17xzuX1liZ6sQ75
TLSHT190B354356B03C9ADDFBD02308F5A6B646721AC490E86B73352F892BD4D642453FDB4E2
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5CE0EA75FEBEBDEB0B811ECD5C831BC62
PackageArchx86_64
PackageDescriptionPure Haskell implementation of SplitMix described in Guy L. Steele, Jr., Doug Lea, and Christine H. Flood. 2014. Fast splittable pseudorandom number generators. In Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications (OOPSLA '14). ACM, New York, NY, USA, 453-472. DOI: <https://doi.org/10.1145/2660193.2660195> The paper describes a new algorithm /SplitMix/ for /splittable/ pseudorandom number generator that is quite fast: 9 64 bit arithmetic/logical operations per 64 bits generated. /SplitMix/ is tested with two standard statistical test suites (DieHarder and TestU01, this implementation only using the former) and it appears to be adequate for "everyday" use, such as Monte Carlo algorithms and randomized data structures where speed is important. In particular, it __should not be used for cryptographic or security applications__, because generated sequences of pseudorandom values are too predictable (the mixing functions are easily inverted, and two successive outputs suffice to reconstruct the internal state).
PackageNameghc-splitmix
PackageReleasedlh.32.4
PackageVersion0.1.0.4
SHA-1077B6C90C147DC041CB7099702A404EC9341FC7E
SHA-2569359E2E506434BBFCAE72BCDAA19B65D74924E032DE563E3946220E44343FC6E
Key Value
MD5F25F3161FAC451861A241E883738012B
PackageArchx86_64
PackageDescriptionPure Haskell implementation of SplitMix described in Guy L. Steele, Jr., Doug Lea, and Christine H. Flood. 2014. Fast splittable pseudorandom number generators. In Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications (OOPSLA '14). ACM, New York, NY, USA, 453-472. DOI: <https://doi.org/10.1145/2660193.2660195> The paper describes a new algorithm /SplitMix/ for /splittable/ pseudorandom number generator that is quite fast: 9 64 bit arithmetic/logical operations per 64 bits generated. /SplitMix/ is tested with two standard statistical test suites (DieHarder and TestU01, this implementation only using the former) and it appears to be adequate for "everyday" use, such as Monte Carlo algorithms and randomized data structures where speed is important. In particular, it __should not be used for cryptographic or security applications__, because generated sequences of pseudorandom values are too predictable (the mixing functions are easily inverted, and two successive outputs suffice to reconstruct the internal state).
PackageNameghc-splitmix
PackageRelease1.6
PackageVersion0.1.0.4
SHA-1DD2B3D011C7D79BE091E2F069B962D367FC063AB
SHA-2565F1CDD26B7B6B868593707D7382FD9A6A92FEF6E8165CAE8E4F10E3FD1ED25AB
Key Value
MD531CEEE105E04D32D95C1DE70EF65D175
PackageArchx86_64
PackageDescriptionPure Haskell implementation of SplitMix described in Guy L. Steele, Jr., Doug Lea, and Christine H. Flood. 2014. Fast splittable pseudorandom number generators. In Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications (OOPSLA '14). ACM, New York, NY, USA, 453-472. DOI: <https://doi.org/10.1145/2660193.2660195> The paper describes a new algorithm /SplitMix/ for /splittable/ pseudorandom number generator that is quite fast: 9 64 bit arithmetic/logical operations per 64 bits generated. /SplitMix/ is tested with two standard statistical test suites (DieHarder and TestU01, this implementation only using the former) and it appears to be adequate for "everyday" use, such as Monte Carlo algorithms and randomized data structures where speed is important. In particular, it __should not be used for cryptographic or security applications__, because generated sequences of pseudorandom values are too predictable (the mixing functions are easily inverted, and two successive outputs suffice to reconstruct the internal state).
PackageMaintainerhttps://bugs.opensuse.org
PackageNameghc-splitmix
PackageRelease1.3
PackageVersion0.1.0.4
SHA-1D754640B525C49BDB9397174A1803217C7FE15EB
SHA-25657736BAE9EF80C10AC610721B9F0EA485B6AFBD1560C05A03CDE132F6B8C7C00