Data filtering using a plurality of hardware accelerators

US2016292209A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2016292209-A1
Application numberUS-201514791832-A
CountryUS
Kind codeA1
Filing dateJul 6, 2015
Priority dateMar 30, 2015
Publication dateOct 6, 2016
Grant date

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

Techniques are provided for data filtering using hardware accelerators. An apparatus comprises a processor, a memory and a plurality of hardware accelerators. The processor is configured to stream data from the memory to a first one of the hardware accelerators and to receive filtered data from a second one of the hardware accelerators. The plurality of hardware accelerators are configured to filter the streamed data utilizing at least one bit vector partitioned across the plurality of hardware accelerators. The hardware accelerators may be field-programmable gate arrays.

First claim

Opening claim text (preview).

What is claimed is: 1 . A method comprising: streaming data from a memory to a first one of a plurality of hardware accelerators; filtering the data in the plurality of hardware accelerators utilizing at least one bit vector partitioned across at least two of the plurality of hardware accelerators; and receiving filtered data from a second one of the plurality of hardware accelerators. 2 . The method of claim 1 , wherein at least one of the plurality of hardware accelerators comprises a field-programmable gate array. 3 . The method of claim 1 , wherein the plurality of hardware accelerators are daisy-chain connected to one another. 4 . The method of claim 3 , wherein filtering the data in the plurality of hardware accelerators comprises, in each of the plurality of hardware accelerators, utilizing one or more hash functions to compute bit vector indices for its corresponding partitioned portion of the at least one bit vector. 5 . The method of claim 3 , further comprising: computing bit vector indices for the at least one bit vector utilizing one or more hash functions in a given one of the plurality of hardware accelerators; and forwarding the bit vector indices for the at least one bit vector to other ones of the plurality of hardware accelerators. 6 . The method of claim 3 , wherein filtering the data in the plurality of hardware accelerators comprises performing a build phase and a probe phase in each of the plurality of hardware accelerators. 7 . The method of claim 6 , wherein performing the build phase comprises: computing one or more hashes of the streamed data; and updating the at least one bit vector if the computed hashes are within a range of a corresponding partitioned portion of the at least one bit vector. 8 . The method of claim 7 , wherein performing the probe phase comprises: probing the at least one bit vector if the computed hashes are within the range of the corresponding partitioned portion of the at least one bit vector; generating one or more probed bit values responsive to the probing; and passing the probed bit values to a next hardware accelerator in the daisy chain. 9 . The method of claim 8 , further comprising filtering the streamed data utilizing the probed bit values in a last one of the hardware accelerators in the daisy chain. 10 . The method of claim 3 , further comprising, in each of the plurality of hardware accelerators: receiving one or more packets each comprising a set of flags and a value, the set of flags comprising a phase flag and two or more match flags; and performing one of a build phase and a probe phase responsive to the value of the phase flag. 11 . The method of claim 10 , wherein the build phase comprises programming each of the plurality of hardware accelerators with a corresponding range of said at least one bit vector. 12 . The method of claim 11 , wherein the probe phase comprises, for a first hardware accelerator in the daisy-chain, setting each of the match flags for a given packet to a first value. 13 . The method of claim 12 , wherein the probe phase comprises, for each hardware accelerator in the daisy-chain: hashing the value of the given packet using two or more hash functions to compute two or more indices, each index corresponding to a respective one of the match flags; verifying whether each of the two or more indices are within the corresponding range of a current hardware accelerator of the daisy-chain; and for each index within the corresponding range of the current hardware accelerator, modifying the corresponding match flag to a second value. 14 . The method of claim 13 , wherein the probe phase comprises, for a last hardware accelerator in the daisy-chain: determining whether each match flag for the given packet is set to the second value; if each match flag for the given packet is set to the second value, streaming the value of the given packet to the processor as filtered data; and if one or more match flags for the given packet is set to the first value, dropping the value of the given packet. 15 . The method of claim 1 , wherein the plurality of hardware accelerators form a Bloom filter.

Assignees

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Classifications

  • Query processing with adaptation to specific hardware, e.g. adapted for using GPUs or SSDs · CPC title

  • Ensuring data consistency and integrity · CPC title

  • Unary operations; Data partitioning operations · CPC title

  • Physics · mapped topic

  • Physics · mapped topic

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What does patent US2016292209A1 cover?
Techniques are provided for data filtering using hardware accelerators. An apparatus comprises a processor, a memory and a plurality of hardware accelerators. The processor is configured to stream data from the memory to a first one of the hardware accelerators and to receive filtered data from a second one of the hardware accelerators. The plurality of hardware accelerators are configured to f…
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification G06F16/2365. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Oct 06 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).