System, method, and recording medium for mirroring matrices for batched Cholesky decomposition on a graphic processing unit

US11036829B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11036829-B2
Application numberUS-201916665313-A
CountryUS
Kind codeB2
Filing dateOct 28, 2019
Priority dateJun 30, 2016
Publication dateJun 15, 2021
Grant dateJun 15, 2021

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Abstract

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A batched Cholesky decomposition method, system, and non-transitory computer readable medium for a Graphics Processing Unit (GPU), include mirroring a second problem matrix of a second problem to a first problem matrix of a first problem as paired matrices and shifting the second problem matrix by N+1 and combining the first problem matrix and the mirrored second problem matrix into one matrix of (N+1)×N, where the first problem shared memory comprises regular intervals, where the second problem shared memory is continuous, and where the GPU performs batched dense Cholesky decomposition with the one matrix from the combining to accelerate the Cholesky decomposition.

First claim

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What is claimed is: 1. A batched Cholesky decomposition method for a Graphics Processing Unit (GPU), the method comprising: mirroring a second problem matrix of a second problem to a first problem matrix of a first problem as paired matrices and shifting the second problem matrix by N+1; and combining the first problem matrix and a mirrored second problem matrix into one matrix that has a memory layout of an (N+1)×N matrix, wherein the first problem matrix and the second problem matrix are two different problems to be solved by Cholesky decomposition simultaneously at a same time to accelerate the Cholesky decomposition, the first problem matrix and the second problem matrix are symmetrical and positive definite matrices, and wherein a linear system is solved via the GPU using the one matrix. 2. The method of claim 1 , wherein the combining solves the linear system by a computer-implemented process. 3. A non-transitory computer-readable recording medium recording a batched Cholesky decomposition program for a Graphics Processing Unit (GPU), the program causing a computer to perform: mirroring a second problem matrix of a second problem to a first problem matrix of a first problem as paired matrices and shifting the second problem matrix by N+1; and combining the first problem matrix and a mirrored second problem matrix into one matrix that has a memory layout of an (N+1)×N matrix, wherein the first problem matrix and the second problem matrix are two different problems to be solved by Cholesky decomposition simultaneously at a same time to accelerate the Cholesky decomposition, the first problem matrix and the second problem matrix are symmetrical and positive definite matrices, and wherein a linear system is solved via the GPU using the one matrix. 4. A batched Cholesky decomposition system on a Graphics Processing Unit (GPU), said system comprising: a processor; and a memory, the memory storing instructions to cause the processor to: mirroring a second problem matrix of a second problem to a first problem matrix of a first problem as paired matrices and shifting the second problem matrix by N+1; and combining the first problem matrix and the mirrored second problem matrix into one matrix that has a memory layout of an (N+1)×N matrix when at least two problems are present to be solved by a processor simultaneously at a same time, the first problem matrix and the second problem matrix are symmetrical and positive definite matrices wherein the GPU performs batched dense Cholesky decomposition with the one matrix from the combining to accelerate the Cholesky decomposition to solve a linear system with the GPU.

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Classifications

  • Processor architectures; Processor configuration, e.g. pipelining · CPC title

  • Indexing scheme relating to group G06F5/00; Methods or arrangements for data conversion without changing the order or content of the data handled · CPC title

  • G06F17/16Primary

    Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

  • Memory management · CPC title

  • having at least two separately controlled shifting levels, e.g. using shifting matrices (G06F5/012 takes precedence) · CPC title

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What does patent US11036829B2 cover?
A batched Cholesky decomposition method, system, and non-transitory computer readable medium for a Graphics Processing Unit (GPU), include mirroring a second problem matrix of a second problem to a first problem matrix of a first problem as paired matrices and shifting the second problem matrix by N+1 and combining the first problem matrix and the mirrored second problem matrix into one matrix …
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification G06F17/16. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jun 15 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).