L-CBF: A Low-Power, Fast Counting Bloom Filter Architecture

Safi, Elham; Moshovos, Andreas; Veneris, Andreas

doi:10.1109/tvlsi.2008.2000244

Cited by 23 publications

(23 citation statements)

References 14 publications

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“…Dharmapurikar et al describe a packet inspection system with hardware-implemented Bloom filters [9]. Often, these designs require efficient implementations of counting Bloom filters [3,24].…”

Section: Related Workmentioning

confidence: 99%

Implementing Signatures for Transactional Memory

Sánchez¹,

Yen²,

Hill³

et al. 2007

40th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2007)

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Transactional Memory (TM) systems must track the read and write sets-items read and written during a transaction-to detect conflicts among concurrent transactions. Several TMs use signatures, which summarize unbounded read/write sets in bounded hardware at a performance cost of false positives (conflicts detected when none exists).This paper examines different organizations to achieve hardware-efficient and accurate TM signatures. First, we find that implementing each signature with a single k-hashfunction Bloom filter (True Bloom signature) is inefficient, as it requires multi-ported SRAMs. Instead, we advocate using k single-hash-function Bloom filters in parallel (Parallel Bloom signature), using area-efficient single-ported SRAMs. Our formal analysis shows that both organizations perform equally well in theory and our simulationbased evaluation shows this to hold approximately in practice. We also show that by choosing high-quality hash functions we can achieve signature designs noticeably more accurate than the previously proposed implementations. Finally, we adapt Pagh and Rodler's cuckoo hashing to implement Cuckoo-Bloom signatures. While this representation does not support set intersection, it mitigates false positives for the common case of small read/write sets and performs like a Bloom filter for large sets.

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Section: Related Workmentioning

confidence: 99%

Implementing Signatures for Transactional Memory

Sánchez¹,

Yen²,

Hill³

et al. 2007

40th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2007)

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show abstract

“…The h i (x) indicates the hash function output. By varying the random number d ij , one may be able to get different hash output [9]. The single hash might lead to false positive.…”

Section: Fig 3: Hash Functionmentioning

confidence: 99%

“…The decoder can be designed using NAND-NOR combination, since it consumes less power compared to any other gates. The counter is preferred to track the multiple line access when the hash output is similar [9]. The up/down counter is needed to enhance the signature updating and for deletion operation.…”

Section: Decoder Modulementioning

confidence: 99%

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Area Efficient Counting Bloom Filter (A-CBF) design for NIDS

Brindha¹,

Senthilkumar²

2013

IJCA

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“…This is a novel application of counting Bloom filters, previously employed for implementing hierarchical store queues [1], coarse-grain coherence [11], snoop filters [12,19], prefetching and data speculation [13], low-energy synonym lookup [20], etc. A low power counting Bloom filter was proposed in [17]. Our design is influenced by the Spectral Bloom filter proposed in [4].…”

Section: Scavenger Architecturementioning

confidence: 99%