公开(公告)号：US20220108182A1

公开(公告)日：2022-04-07

申请号：US17551170

申请日：2021-12-14

Applicant: Intel Corporation

Inventor： Todd A. Anderson ,  Shengtian Zhou ,  Javier Turek ,  Celine Lee ,  Justin Gottschlich

IPC: G06N3/08 ,  G06F40/30 ,  G06N3/04

Abstract: Methods and apparatus to train models for program synthesis are disclosed. A disclosed example apparatus includes at least one memory, instructions, and processor circuitry. The processor circuitry is to execute the instructions to sample pairs of programs, the pairs of programs including first programs and second programs, the first programs including natural language descriptions and second programs, calculate program similarity scores corresponding to the pairs of programs, and train a model based on entries corresponding to ones of the pairs of programs, at least one of the entries including a corresponding one of the natural language descriptions with a paired one of the second programs, and a corresponding one of the program similarity scores.

公开(公告)号：US12032541B2

公开(公告)日：2024-07-09

申请号：US17540050

申请日：2021-12-01

Applicant: Intel Corporation

Inventor： Niranjan Hasabnis ,  Justin Gottschlich ,  Celine Lee ,  Emine Tatbul Bitim ,  Shengtian Zhou

IPC: G06F16/215

CPC classification number: G06F16/215

Abstract: Methods, apparatus, systems, and articles of manufacture to improve data quality for artificial intelligence are disclosed. An example apparatus includes an interface; instructions; and processor circuitry to execute the instruction to: determine an indirect quality of a repository that include datapoints of a dataset; determine a direct quality of the repository that include the datapoints of the dataset; determine a dataset quality based on the indirect quality of the repository and the direct quality of the repository; and when the quality does not satisfy a threshold, filter out a subset of the datapoints to prepare the dataset to support the training of the neural network.

公开(公告)号：US12001382B2

公开(公告)日：2024-06-04

申请号：US17559556

申请日：2021-12-22

Applicant: Intel Corporation

Inventor： Celine Lee ,  Niranjan Hasabnis ,  Paul Petersen ,  Justin Gottschlich ,  Ramesh Peri

IPC: G06F15/80 ,  G06F3/06 ,  G06F9/455 ,  G06F9/48 ,  G06F9/50 ,  G06F13/40 ,  G06N3/006 ,  G06N3/045 ,  G06N3/08 ,  G06N3/084 ,  G06N5/01 ,  G06N20/00

CPC classification number: G06F15/80 ,  G06F13/4068 ,  G06N20/00

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate command lists to be offloaded to accelerator circuitry. An example apparatus includes kernel duration model circuitry to predict a duration of execution of a first kernel based on a first source location, a first name, a first property of a first argument, or an occupancy of the first kernel. The example apparatus includes subsequent kernel model circuitry to predict a tuple and a dependency of a second kernel based on a second source location, a second name, a second property of a second argument, or a time of submission of the previous kernel. The example apparatus includes reinforcement learning model circuitry to determine whether to bundle the first kernel into a command list based on the duration of execution of the first kernel, the tuple of the second kernel, or the dependency of the second kernel.

公开(公告)号：US11977605B2

公开(公告)日：2024-05-07

申请号：US17644328

申请日：2021-12-14

Applicant: Intel Corporation

Inventor： Justin Gottschlich ,  Niranjan Hasabnis ,  Paul Petersen ,  Shengtian Zhou ,  Celine Lee

IPC: G06F11/36 ,  G06F8/71 ,  G06F8/75 ,  G06F9/451 ,  G06F18/214 ,  G06F18/22 ,  G06F18/2413 ,  G06N3/08 ,  G06F16/9535 ,  G06Q30/0282

CPC classification number: G06F18/22 ,  G06F8/71 ,  G06F8/75 ,  G06F9/453 ,  G06F18/214 ,  G06F18/2155 ,  G06F18/24147 ,  G06N3/08 ,  G06F16/9535 ,  G06Q30/0282

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed that implement an automatically evolving code recommendation engine. In one example, the apparatus collects a user code snippet. The apparatus then determines a structured representation of the user code snippet. Next, the apparatus generates a recommended code snippet using the structured representation of the user code snippet. Then the apparatus obtains user-determined code snippet feedback comparing the user code snippet to the recommended code snippet, the user-determined code snippet feedback indicating one of a match, no match, or uncertain. Finally, the apparatus stores a code snippet training pair in a training database, the code snippet training pair including the user code snippet and the recommended code snippet.

公开(公告)号：US11782813B2

公开(公告)日：2023-10-10

申请号：US17554918

申请日：2021-12-17

Applicant: Intel Corporation

Inventor： Shengtian Zhou ,  Justin Gottschlich ,  Fangke Ye ,  Celine Lee ,  Jesmin Jahan Tithi

IPC: G06F11/36 ,  G06N3/08

CPC classification number: G06F11/3608 ,  G06F11/362 ,  G06F11/3688 ,  G06N3/08

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to determine refined context for bug detection. At least one non-transitory machine-readable medium includes instructions that, when executed, cause at least one processor to at least classify a node on a graph, the graph to represent a computer program, the node to contain partial bug context corresponding to the computer program; identify a location of a software bug in the computer program, the location based on the node; determine a static bug context of the software bug using the location of the software bug; determine a dynamic bug context of the software bug using the location of the software bug; and determine a refined bug context based on a merge of the static bug context and the dynamic bug context.

公开(公告)号：US20220334835A1

公开(公告)日：2022-10-20

申请号：US17644328

申请日：2021-12-14

Applicant: Intel Corporation

Inventor： Justin Gottschlich ,  Niranjan Hasabnis ,  Paul Petersen ,  Shengtian Zhou ,  Celine Lee

IPC: G06F8/75 ,  G06K9/62 ,  G06N3/08

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed that implement an automatically evolving code recommendation engine. In one example, the apparatus collects a user code snippet. The apparatus then determines a structured representation of the user code snippet. Next, the apparatus generates a recommended code snippet using the structured representation of the user code snippet. Then the apparatus obtains user-determined code snippet feedback comparing the user code snippet to the recommended code snippet, the user-determined code snippet feedback indicating one of a match, no match, or uncertain. Finally, the apparatus stores a code snippet training pair in a training database, the code snippet training pair including the user code snippet and the recommended code snippet.

公开(公告)号：US20220114137A1

公开(公告)日：2022-04-14

申请号：US17559556

申请日：2021-12-22

Applicant: Intel Corporation

Inventor： Celine Lee ,  Niranjan Hasabnis ,  Paul Petersen ,  Justin Gottschlich ,  Ramesh Peri

IPC: G06F15/80 ,  G06N20/00 ,  G06F13/40

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate command lists to be offloaded to accelerator circuitry. An example apparatus includes kernel duration model circuitry to predict a duration of execution of a first kernel based on a first source location, a first name, a first property of a first argument, or an occupancy of the first kernel. The example apparatus includes subsequent kernel model circuitry to predict a tuple and a dependency of a second kernel based on a second source location, a second name, a second property of a second argument, or a time of submission of the previous kernel. The example apparatus includes reinforcement learning model circuitry to determine whether to bundle the first kernel into a command list based on the duration of execution of the first kernel, the tuple of the second kernel, or the dependency of the second kernel.

公开(公告)号：US20220114076A1

公开(公告)日：2022-04-14

申请号：US17554918

申请日：2021-12-17

Applicant: Intel Corporation

Inventor： Shengtian Zhou ,  Justin Gottschlich ,  Fangke Ye ,  Celine Lee

IPC: G06F11/36 ,  G06N3/08

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to determine refined context for bug detection. At least one non-transitory machine-readable medium includes instructions that, when executed, cause at least one processor to at least classify a node on a graph, the graph to represent a computer program, the node to contain partial bug context corresponding to the computer program; identify a location of a software bug in the computer program, the location based on the node; determine a static bug context of the software bug using the location of the software bug; determine a dynamic bug context of the software bug using the location of the software bug; and determine a refined bug context based on a merge of the static bug context and the dynamic bug context.

公开(公告)号：US20220092042A1

公开(公告)日：2022-03-24

申请号：US17540050

申请日：2021-12-01

Applicant: Intel Corporation

Inventor： Niranjan Hasabnis ,  Justin Gottschlich ,  Celine Lee ,  Emine Tatbul Bitim ,  Shengtian Zhou

IPC: G06F16/215

Abstract: Methods, apparatus, systems, and articles of manufacture to improve data quality for artificial intelligence are disclosed. An example apparatus includes an interface; instructions; and processor circuitry to execute the instruction to: determine an indirect quality of a repository that include datapoints of a dataset; determine a direct quality of the repository that include the datapoints of the dataset; determine a dataset quality based on the indirect quality of the repository and the direct quality of the repository; and when the quality does not satisfy a threshold, filter out a subset of the datapoints to prepare the dataset to support the training of the neural network.