公开(公告)号：US12073250B2

公开(公告)日：2024-08-27

申请号：US17318795

申请日：2021-05-12

Applicant: Oracle International Corporation

Inventor： Wei Jiang ,  Guang C. Wang ,  Kenny C. Gross

IPC: G06F9/50 ,  G06F9/455 ,  G06N20/00

CPC classification number: G06F9/5016 ,  G06F9/45558 ,  G06F9/5044 ,  G06N20/00 ,  G06F2009/4557 ,  G06F2009/45591

Abstract: We disclose a system that executes an inferential model in VRAM that is embedded in a set of graphics-processing units (GPUs). The system obtains execution parameters for the inferential model specifying: a number of signals, a number of training vectors, a number of observations and a desired data precision. It also obtains one or more formulae for computing memory usage for the inferential model based on the execution parameters. Next, the system uses the one or more formulae and the execution parameters to compute an estimated memory footprint for the inferential model. The system uses the estimated memory footprint to determine a required number of GPUs to execute the inferential model, and generates code for executing the inferential model in parallel while efficiently using available memory in the required number of GPUs. Finally, the system uses the generated code to execute the inferential model in the set of GPUs.

公开(公告)号：US11726160B2

公开(公告)日：2023-08-15

申请号：US17694304

申请日：2022-03-14

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. Wetherbee ,  Andrew Lewis ,  Michael Dayringer ,  Guang C. Wang ,  Kenny C. Gross

IPC: G01R35/00 ,  G01R29/08

CPC classification number: G01R35/005 ,  G01R29/0814 ,  G01R29/0892

Abstract: Systems, methods, and other embodiments associated with automated calibration in electromagnetic scanners are described. In one embodiment, a method includes: detecting one or more peak frequency bands in electromagnetic signals collected by the electromagnetic scanner at a geographic location; comparing the one or more peak frequency bands to broadcast frequencies assigned to local radio stations of the geographic location; and indicating that the electromagnetic scanner is calibrated by finding at least one match between one peak frequency band of the peak frequency bands and one of the broadcast frequencies. An electromagnetic scanner may be recalibrated based on comparing the one or more peak frequency bands to broadcast frequencies.

公开(公告)号：US20230137596A1

公开(公告)日：2023-05-04

申请号：US17716489

申请日：2022-04-08

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Matthew T. Gerdes ,  James Rohrkemper ,  Sanjeev R. Sondur ,  Kenny C. Gross ,  Guang C. Wang

IPC: H05K7/20

Abstract: Systems, methods, and other embodiments associated with unified control of cooling in computers are described. In one embodiment, a method locks operation of first and second cooling mechanisms configured to cool one or more components in the computer. In response to a first condition, the method unlocks the operation of the first cooling mechanism to allow the first cooling mechanism to make cooling adjustments while the operation of the second cooling mechanism is locked. In response to a second condition, the method unlocks the operation of the second cooling mechanism to allow the second cooling mechanism to make cooling adjustments while the operation of the first cooling mechanism is locked. In the method, the first cooling mechanism and the second cooling mechanism are prevented from making the cooling adjustments simultaneously.

公开(公告)号：US20220383043A1

公开(公告)日：2022-12-01

申请号：US17334392

申请日：2021-05-28

Applicant: Oracle International Corporation

Inventor： Matthew T. Gerdes ,  Guang C. Wang ,  Kenny C. Gross ,  Timothy David Cline

IPC: G06K9/62 ,  G06K9/00

Abstract: The disclosed system produces synthetic signals for testing machine-learning systems. During operation, the system generates a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is a combination of multiple constituent sinusoidal signals with different periodicities. Next, the system adds time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods. The system also multiplies each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods. Finally, the system adds time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods. The time-varying random noise values, amplitude values and mean values can be selected through a roll-of-the-die process from a library of values, which are learned from industry-specific signals.

公开(公告)号：US11487640B2

公开(公告)日：2022-11-01

申请号：US16128071

申请日：2018-09-11

Applicant: Oracle International Corporation

Inventor： Kenny C. Gross ,  Guang C. Wang

IPC: G06F11/34 ,  G06N20/00 ,  G06N5/04 ,  G06K9/62

Abstract: During operation, the system obtains the time-series sensor signals, which were gathered from sensors in a monitored system. Next, the system classifies the time-series sensor signals into stair-stepped signals and un-stair-stepped signals. The system then replaces stair-stepped values in the stair-stepped signals with interpolated values determined from un-stair-stepped values in the stair-stepped signals. Next, the system divides the time-series sensor data into a training set and an estimation set. The system then trains an inferential model on the training set, and uses the trained inferential model to replace interpolated values in the estimation set with inferential estimates. Next, the system switches roles of the training and estimation sets to produce a new training set and a new estimation set. The system then trains the inferential model on the new training set, and uses the trained inferential model to replace interpolated values in the new estimation set with inferential estimates.

公开(公告)号：US11120134B2

公开(公告)日：2021-09-14

申请号：US16384722

申请日：2019-04-15

Applicant: Oracle International Corporation

Inventor： Andrew J. Lewis ,  Kenny C. Gross ,  Michael H. S. Dayringer ,  Guang C. Wang

IPC: G06F21/00 ,  G06F21/56 ,  G06F17/14 ,  G01R31/28 ,  G06F21/71

Abstract: The disclosed embodiments provide a system that detects unwanted electronic components in a target computing system. During operation, the system obtains target electromagnetic interference (EMI) signals, which were gathered by monitoring EMI signals generated by the target computing system, using an insertable device, wherein when the insertable device is inserted into the target computing system, the insertable device gathers the target EMI signals from the target computing system. Next, the system generates a target EMI fingerprint from the target EMI signals. Finally, the system compares the target EMI fingerprint against a reference EMI fingerprint for the target computing system to determine whether the target computing system contains any unwanted electronic components.

公开(公告)号：US10984106B2

公开(公告)日：2021-04-20

申请号：US16419861

申请日：2019-05-22

Applicant: Oracle International Corporation

Inventor： Kenny C. Gross ,  Andrew J. Lewis ,  Guang C. Wang ,  Michael H. S. Dayringer

IPC: G06F21/56 ,  G06F11/30 ,  G01R29/08

Abstract: The disclosed embodiments provide a system that detects execution of malicious cryptomining software in a target computing system. During operation, the system monitors target electromagnetic interference (EMI) signals generated during operation of the target computing system. Next, the system generates a target EMI fingerprint from the target EMI signals. The system then compares the target EMI fingerprint against a set of malicious EMI fingerprints for different pieces of malicious cryptomining software to determine whether the target computing system is executing malicious cryptomining software.

公开(公告)号：US12260304B2

公开(公告)日：2025-03-25

申请号：US17205445

申请日：2021-03-18

Applicant: Oracle International Corporation

Inventor： Neelesh Kumar Shukla ,  Saurabh Thapliyal ,  Matthew T. Gerdes ,  Guang C. Wang ,  Kenny C. Gross

IPC: G06N20/00 ,  G06F18/21 ,  G06N5/04

Abstract: The disclosed embodiments provide a system that detects sensor anomalies in a univariate time-series signal. During a surveillance mode, the system receives the univariate time-series signal from a sensor in a monitored system. Next, the system performs a staggered-sampling operation on the univariate time-series signal to produce N sub-sampled time-series signals, wherein the staggered-sampling operation allocates consecutive samples from the univariate time-series signal to the N sub-sampled time-series signals in a round-robin ordering. The system then uses a trained inferential model to generate estimated values for the N sub-sampled time-series signals based on cross-correlations with other sub-sampled time-series signals. Next, the system performs an anomaly detection operation to detect incipient sensor anomalies in the univariate time-series signal based on differences between actual values and the estimated values for the N sub-sampled time-series signals. Whenever an incipient sensor anomaly is detected, the system generates a notification.

公开(公告)号：US11860974B2

公开(公告)日：2024-01-02

申请号：US17090112

申请日：2020-11-05

Applicant: Oracle International Corporation

Inventor： Guang C. Wang ,  Kenny C. Gross ,  Zexi Chen

IPC: G06F18/00 ,  G06F18/214 ,  G06F11/30 ,  H04L9/40 ,  G06N5/04 ,  G06F18/231 ,  G06N7/01

CPC classification number: G06F18/2148 ,  G06F11/3075 ,  G06F11/3089 ,  G06F18/231 ,  G06N5/04 ,  G06N7/01 ,  H04L63/1416 ,  H04L63/1425

Abstract: A system is provided for training an inferential model based on selected training vectors. During operation, the system receives training data comprising observations for a set of time-series signals gathered from sensors in a monitored system during normal fault-free operation. Next, the system divides the observations into N subgroups comprising non-overlapping time windows of observations. The system then selects observations with a local minimum value and a local maximum value for all signals from each subgroup to be training vectors for the inferential model. Finally, the system trains the inferential model using the selected training vectors. Note that by selecting observations with local minimum and maximum values to be training vectors, the system maximizes an operational range for the training vectors, which reduces clipping in estimates subsequently produced by the inferential model and thereby reduces false alarms.

公开(公告)号：US11729940B2

公开(公告)日：2023-08-15

申请号：US17716489

申请日：2022-04-08

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Matthew T. Gerdes ,  James Rohrkemper ,  Sanjeev R. Sondur ,  Kenny C. Gross ,  Guang C. Wang

IPC: G06F1/16 ,  H05K5/00 ,  H05K7/00 ,  H05K7/20

CPC classification number: H05K7/20209 ,  H05K7/207 ,  H05K7/20136 ,  H05K7/20627

Abstract: Systems, methods, and other embodiments associated with unified control of cooling in computers are described. In one embodiment, a method locks operation of first and second cooling mechanisms configured to cool one or more components in the computer. In response to a first condition, the method unlocks the operation of the first cooling mechanism to allow the first cooling mechanism to make cooling adjustments while the operation of the second cooling mechanism is locked. In response to a second condition, the method unlocks the operation of the second cooling mechanism to allow the second cooling mechanism to make cooling adjustments while the operation of the first cooling mechanism is locked. In the method, the first cooling mechanism and the second cooling mechanism are prevented from making the cooling adjustments simultaneously.