Abstract: An optical code scanner being operated using an algorithm is provided. The scanner may scan an optical label. The label may include machine-readable code. The scanner may derive a single set of instructions from the code or multiple sets of instructions from the code. The scanner may process the code. The processing may upload a set of instructions from the code to the scanner and store the set of instructions in an instructions library. The scanner may also derive a picture associated with the instructions and store the picture in the library. The scanner may display a plurality of pictures. Each of the pictures may correspond to a set of uploaded instructions stored on the scanner. Each of the plurality of pictures may be selectable by a user. In response to a user selection of a picture, the scanner may be configured to execute the uploaded instructions that correspond to the selected picture.

Abstract: A batched Cholesky decomposition method, system, and non-transitory computer readable medium for a Graphics Processing Unit (GPU), include mirroring matrices to form paired matrices solving the paired matrices simultaneously.

Abstract: Software tools disclosed herein may allow a user to enter design choices that alter an aesthetic appearance of a machine-readable label such that modules included in the label deviate from a standardized definition for the modules. Such alterations may include changes in size, color and orientation of modules. The alterations may allow a user to create machine-readable labels having unique aesthetic appearances. A software engine may ensure that, despite the aesthetic design choices entered by a user, the generated machine-readable label is reliably scannable.

Abstract: A batched Cholesky decomposition method, system, and non-transitory computer readable medium for a Graphics Processing Unit (GPU), include mirroring matrices to form paired matrices solving the paired matrices simultaneously.

Abstract: An optical code scanner being operated using an algorithm is provided. The scanner may scan an optical label. The label may include machine-readable code. The scanner may derive a single set of instructions from the code or multiple sets of instructions from the code. The scanner may process the code. The processing may upload a set of instructions from the code to the scanner and store the set of instructions in an instructions library. The scanner may also derive a picture associated with the instructions and store the picture in the library. The scanner may display a plurality of pictures. Each of the pictures may correspond to a set of uploaded instructions stored on the scanner. Each of the plurality of pictures may be selectable by a user. In response to a user selection of a picture, the scanner may be configured to execute the uploaded instructions that correspond to the selected picture.

Abstract: An optical code scanner being operated using an algorithm is provided. The scanner may scan an optical label. The label may include machine-readable code. The scanner may derive a single set of instructions from the code or multiple sets of instructions from the code. The scanner may process the code. The processing may upload a set of instructions from the code to the scanner and store the set of instructions in an instructions library. The scanner may also derive a picture associated with the instructions and store the picture in the library. The scanner may display a plurality of pictures. Each of the pictures may correspond to a set of uploaded instructions stored on the scanner. Each of the plurality of pictures may be selectable by a user. In response to a user selection of a picture, the scanner may be configured to execute the uploaded instructions that correspond to the selected picture.

Abstract: An optical code scanner being operated using an algorithm is provided. The scanner may scan an optical label. The label may include machine-readable code. The scanner may derive a single set of instructions from the code or multiple sets of instructions from the code. The scanner may process the code. The processing may upload a set of instructions from the code to the scanner and store the set of instructions in an instructions library. The scanner may also derive a picture associated with the instructions and store the picture in the library. The scanner may display a plurality of pictures. Each of the pictures may correspond to a set of uploaded instructions stored on the scanner. Each of the plurality of pictures may be selectable by a user. In response to a user selection of a picture, the scanner may be configured to execute the uploaded instructions that correspond to the selected picture.

Abstract: Software tools disclosed herein may allow a user to enter design choices that alter an aesthetic appearance of a machine-readable label such that modules included in the label deviate from a standardized definition for the modules. Such alterations may include changes in size, color and orientation of modules. The alterations may allow a user to create machine-readable labels having unique aesthetic appearances. A software engine may ensure that, despite the aesthetic design choices entered by a user, the generated machine-readable label is reliably scannable.

Abstract: Software tools disclosed herein may allow a user to enter design choices that alter an aesthetic appearance of a machine-readable label such that modules included in the label deviate from a standardized definition for the modules. Such alterations may include changes in size, color and orientation of modules. The alterations may allow a user to create machine-readable labels having unique aesthetic appearances. A software engine may ensure that, despite the aesthetic design choices entered by a user, the generated machine-readable label is reliably scannable.

Abstract: A batched Cholesky decomposition method, system, and non-transitory computer readable medium for a Graphics Processing Unit (GPU), include mirroring matrices to form paired matrices solving the paired matrices simultaneously.

Abstract: 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.

Abstract: Software tools disclosed herein may allow a user to enter design choices that alter an aesthetic appearance of a machine-readable label such that modules included in the label deviate from a standardized definition for the modules. Such alterations may include changes in size, color and orientation of modules. The alterations may allow a user to create machine-readable labels having unique aesthetic appearances. A software engine may ensure that, despite the aesthetic design choices entered by a user, the generated machine-readable label is reliably scannable.

Abstract: An iterative graph algorithm accelerating method, system, and computer program product, include recording an order of access nodes in a memory layout, reordering the access nodes in the memory layout in accordance with the recorded order, and updating edge information of the reordered access nodes.

Abstract: 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 by merging the first problem matrix and the mirrored second problem matrix. The first problem matrix and the second problem matrix are symmetric and positive definite matrices.

Abstract: 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.

Abstract: 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 by merging the first problem matrix and the mirrored second problem matrix. The first problem matrix and the second problem matrix are symmetric and positive definite matrices.

Abstract: 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 by N+1, combining the first problem matrix and the mirrored second problem matrix into one matrix of (N+1)×N, and reading the fixed size data length of the one square matrix with a fixed data interval for both the first problem and the second problem.

Abstract: An iterative graph algorithm accelerating method, system, and computer program product, include recording an order of access nodes in a memory layout, reordering the access nodes in the memory layout in accordance with the recorded order, and updating edge information of the reordered access nodes.