Perfect Hash Function Generation on the GPU with RecSplit

Minimale perfekte Hashfunktionen (MPHFs) bilden eine statische Menge S von beliebigen Schlüsseln auf die Menge der ersten |S| natürlichen Zahlen bijektiv ab, d. h., jeder Hashwert wird exakt einmal verwendet. Sie sind in vielen Anwendungen hilfreich, zum Beispiel, um Hashtabellen mit garantiert konstanter Zugriffszeit zu implementieren. MPHFs können sehr kompakt sein — weniger als 2 Bit pro Schlüssel sind möglich. Andererseits sind MPHFs nicht in der Lage zu entscheiden, ob ein gegebener Schlüssel zu S gehört. Zurzeit ist RecSplit die speichereffizienteste MPHF. RecSplit bietet verschiedene Kompromisse zwischen Platzverbrauch, Konstruktionszeit und Anfragezeit an. RecSplit kann zum Beispiel eine MPHF mit 1.56 Bits pro Schlüssel in weniger als 2 ms pro Schlüssel konstruieren. Das ist jedoch zu langsam für große Eingaben. Diese Arbeit präsentiert neue RecSplit-Implementierungen, die Multithreading, SIMD und die Leistung von GPUs nutzen, um die Konstruktionszeit zu verbessern. Gemeinsam mit unserer neuen bijection-rotation-Methode erreichen wir Beschleunigungen um Faktoren bis zu 333 für unsere SIMD-Implementierung auf einer 8-Kern CPU und bis zu 1873 für unsere GPU-Implementierung verglichen mit der originalen, sequenziellen RecSplit-Implementierung. Dadurch können wir MPHFs mit 1.56 Bits pro Schlüssel in weniger als 1.5 μs pro Schlüssel konstruieren

High Performance Construction of RecSplit Based Minimal Perfect Hash Functions

A minimal perfect hash function (MPHF) bijectively maps a set S of objects to the first |S| integers. It can be used as a building block in databases and data compression. RecSplit [Esposito et al., ALENEX\u2720] is currently the most space efficient practical minimal perfect hash function. It heavily relies on trying out hash functions in a brute force way. We introduce rotation fitting, a new technique that makes the search more efficient by drastically reducing the number of tried hash functions. Additionally, we greatly improve the construction time of RecSplit by harnessing parallelism on the level of bits, vectors, cores, and GPUs. In combination, the resulting improvements yield speedups up to 239 on an 8-core CPU and up to 5438 using a GPU. The original single-threaded RecSplit implementation needs 1.5 hours to construct an MPHF for 5 Million objects with 1.56 bits per object. On the GPU, we achieve the same space usage in just 5 seconds. Given that the speedups are larger than the increase in energy consumption, our implementation is more energy efficient than the original implementation

High Performance Construction of RecSplit Based Minimal Perfect Hash Functions

A minimal perfect hash function (MPHF) bijectively maps a set S of objects to the first |S| integers. It can be used as a building block in databases and data compression. RecSplit [Esposito et al., ALENEX\u2720] is currently the most space efficient practical minimal perfect hash function. It heavily relies on trying out hash functions in a brute force way. We introduce rotation fitting, a new technique that makes the search more efficient by drastically reducing the number of tried hash functions. Additionally, we greatly improve the construction time of RecSplit by harnessing parallelism on the level of bits, vectors, cores, and GPUs. In combination, the resulting improvements yield speedups up to 239 on an 8-core CPU and up to 5438 using a GPU. The original single-threaded RecSplit implementation needs 1.5 hours to construct an MPHF for 5 Million objects with 1.56 bits per object. On the GPU, we achieve the same space usage in just 5 seconds. Given that the speedups are larger than the increase in energy consumption, our implementation is more energy efficient than the original implementation

High Performance Construction of RecSplit Based Minimal Perfect Hash Functions

A minimal perfect hash function (MPHF) bijectively maps a set S of objects to the first |S| integers. It can be used as a building block in databases and data compression. RecSplit [Esposito et al., ALENEX'20] is currently the most space efficient practical minimal perfect hash function. It heavily relies on trying out hash functions in a brute force way. We introduce rotation fitting, a new technique that makes the search more efficient by drastically reducing the number of tried hash functions. Additionally, we greatly improve the construction time of RecSplit by harnessing parallelism on the level of bits, vectors, cores, and GPUs. In combination, the resulting improvements yield speedups up to 239 on an 8-core CPU and up to 5438 using a GPU. The original single-threaded RecSplit implementation needs 1.5 hours to construct an MPHF for 5 Million objects with 1.56 bits per object. On the GPU, we achieve the same space usage in just 5 seconds. Given that the speedups are larger than the increase in energy consumption, our implementation is more energy efficient than the original implementation

Resumos em andamento - Saúde Coletiva

Resumos em andamento - Saúde Coletiv

Resumos em andamento - Saúde Coletiva

Resumos em andamento - Saúde Coletiv

Resumos concluídos - Saúde Coletiva

Resumos concluídos - Saúde Coletiv