The computation of a peeling order in a randomly generated hypergraph is the most time- consuming step in a number of constructions, such as perfect hashing schemes, random r-SAT solvers, error-correcting codes, and approximate set encodings. While there exists a straightforward linear time algorithm, its poor I/O performance makes it impractical for hypergraphs whose size exceeds the available internal memory. We show how to reduce the computation of a peeling order to a small number of sequential scans and sorts, and analyze its I/O complexity in the cache-oblivious model. The resulting algorithm requires O(sort(n)) I/Os and O(n log n) time to peel a random hypergraph with n edges. We experimentally evaluate the performance of our implementation of this algorithm in a real- world scenario by using the construction of minimal perfect hash functions (MPHF) as our test case: our algorithm builds a MPHF of 7.6 billion keys in less than 21 hours on a single machine. The resulting data structure is both more space-efficient and faster than that obtained with the current state-of-the-art MPHF construction for large-scale key sets.

Cache-oblivious peeling of random hypergraphs

Venturini R;
2014

Abstract

The computation of a peeling order in a randomly generated hypergraph is the most time- consuming step in a number of constructions, such as perfect hashing schemes, random r-SAT solvers, error-correcting codes, and approximate set encodings. While there exists a straightforward linear time algorithm, its poor I/O performance makes it impractical for hypergraphs whose size exceeds the available internal memory. We show how to reduce the computation of a peeling order to a small number of sequential scans and sorts, and analyze its I/O complexity in the cache-oblivious model. The resulting algorithm requires O(sort(n)) I/Os and O(n log n) time to peel a random hypergraph with n edges. We experimentally evaluate the performance of our implementation of this algorithm in a real- world scenario by using the construction of minimal perfect hash functions (MPHF) as our test case: our algorithm builds a MPHF of 7.6 billion keys in less than 21 hours on a single machine. The resulting data structure is both more space-efficient and faster than that obtained with the current state-of-the-art MPHF construction for large-scale key sets.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
DCC 2014 - Data Compression Conference
352
361
978-1-4799-3882-7
Sì, ma tipo non specificato
26-28 March 2014
Snowbird, Utah, USA
Perfect hash functions
Hypergraph algorithms
Cache-oblivious algorithms
Il codice commessa corretto è ICT.P09.006.001 - 074 - Tecnologie avanzate, Sistemi e Servizi per Grid
1
restricted
Belazzougui D.; Boldi P.; Ottaviano G.; Venturini R.; Vigna S.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
File in questo prodotto:
File Dimensione Formato  
prod_282742-doc_80631.pdf

solo utenti autorizzati

Descrizione: Cache-oblivious peeling of random hypergraphs
Tipologia: Versione Editoriale (PDF)
Dimensione 308.77 kB
Formato Adobe PDF
308.77 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
prod_282742-doc_80632.pdf

solo utenti autorizzati

Descrizione: Cache-oblivious peeling of random hypergraphs-1
Tipologia: Versione Editoriale (PDF)
Dimensione 221.7 kB
Formato Adobe PDF
221.7 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/245103
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 24
  • ???jsp.display-item.citation.isi??? ND
social impact