公开(公告)号：US11853214B2

公开(公告)日：2023-12-26

申请号：US18071291

申请日：2022-11-29

申请人： eBay Inc.

发明人： Amit Desai

IPC分类号： G06F12/0802 ,  H03M7/30

CPC分类号： G06F12/0802 ,  H03M7/70 ,  G06F2212/1044 ,  G06F2212/608

摘要： A method for compressing data in a local cache of a web server is described. A local cache compression engine accesses values in the local cache and determines a cardinality of the values of the local cache. The local cache compression engine determines a compression rate of a compression algorithm based on the cardinality of the values of the local cache. The compression algorithm is applied to the cache based on the compression rate to generate a compressed local cache.

公开(公告)号：US11769570B2

公开(公告)日：2023-09-26

申请号：US17445202

申请日：2021-08-17

申请人： City University of Hong Kong

发明人： Zhenhao Sun ,  Meng Wang ,  Shiqi Wang ,  Tak Wu Sam Kwong

IPC分类号： H03M7/34 ,  G16B50/50 ,  G16B40/20 ,  H03M7/30 ,  G06F16/22 ,  G06N7/01

CPC分类号： G16B50/50 ,  G06F16/2255 ,  G06N7/01 ,  G16B40/20 ,  H03M7/6011 ,  H03M7/70

摘要： Systems and methods for genome sequence compression and decompression are provided. The method for compression encoding of a genome sequence includes partitioning a genome sequence into a plurality of Group of Bases (GoBs) and processing each of the plurality of GoBs independently to encode the genome sequence into a bit stream. Processing each of the plurality of GoBs includes dividing each of the plurality of GOBs into a first part and a second part, the first part including an initial context part and the second part including a learning-based inference part. The processing each of the plurality of GoBs further includes encoding the first part in accordance with a Markov model, encoding the second part in accordance with a learning-based model, and encoding the encoded first part and the encoded second part into the bit stream with an arithmetic encoder. The learning-based model may include Long and Short-Term Memory (LSTM)-based neural networks.

公开(公告)号：US11750212B2

公开(公告)日：2023-09-05

申请号：US17232074

申请日：2021-04-15

申请人： MICROSOFT TECHNOLOGY LICENSING, LLC

发明人： Amol Ashok Ambardekar ,  Aleksandar Tomic ,  Chad Balling McBride ,  George Petre ,  Kent D. Cedola ,  Larry Marvin Wall ,  Boris Bobrov

IPC分类号： G06N3/04 ,  G06F9/46 ,  H03M7/30 ,  G06N3/063 ,  G06F12/0862 ,  G06F1/324 ,  G06F3/06 ,  G06F9/38 ,  G06F12/08 ,  G06F12/10 ,  G06F15/80 ,  G06F17/15 ,  G06N3/049 ,  G06N3/06 ,  G06N3/08 ,  G06N3/10 ,  H04L45/02 ,  H04L67/02 ,  G06F9/30 ,  H04L67/1001 ,  G06F9/48 ,  G06F12/02 ,  G06N3/045 ,  G06N3/065 ,  G06F13/16 ,  G06F1/3234 ,  G06F13/28 ,  H03M7/46 ,  H04L45/50

CPC分类号： H03M7/3059 ,  G06F1/324 ,  G06F1/3275 ,  G06F3/0604 ,  G06F3/067 ,  G06F3/0631 ,  G06F9/30087 ,  G06F9/3836 ,  G06F9/3887 ,  G06F9/46 ,  G06F9/4881 ,  G06F12/0207 ,  G06F12/0238 ,  G06F12/08 ,  G06F12/0862 ,  G06F12/10 ,  G06F13/1673 ,  G06F13/1689 ,  G06F13/28 ,  G06F15/8007 ,  G06F17/15 ,  G06N3/04 ,  G06N3/045 ,  G06N3/049 ,  G06N3/06 ,  G06N3/063 ,  G06N3/065 ,  G06N3/08 ,  G06N3/10 ,  H03M7/6005 ,  H03M7/6011 ,  H03M7/70 ,  H04L45/04 ,  H04L67/02 ,  H04L67/1001 ,  G06F2209/484 ,  G06F2209/485 ,  G06F2212/657 ,  H03M7/46 ,  H04L45/50 ,  Y02D10/00

摘要： The performance of a neural network (NN) and/or deep neural network (DNN) can limited by the number of operations being performed as well as memory data management of a NN/DNN. Using vector quantization of neuron weight values, the processing of data by neurons can be optimize the number of operations as well as memory utilization to enhance the overall performance of a NN/DNN. Operatively, one or more contiguous segments of weight values can be converted into one or more vectors of arbitrary length and each of the one or more vectors can be assigned an index. The generated indexes can be stored in an exemplary vector quantization lookup table and retrieved by exemplary fast weight lookup hardware at run time on the fly as part of an exemplary data processing function of the NN as part of an inline de-quantization operation to obtain needed one or more neuron weight values.

公开(公告)号：US20230261673A1

公开(公告)日：2023-08-17

申请号：US18168932

申请日：2023-02-14

申请人： Zibra AI, Inc.

发明人： Vladyslav Zavadskyi

IPC分类号： H03M7/30

CPC分类号： H03M7/70

摘要： By one approach, these teachings provide for a data compression apparatus comprising a memory having data to be compressed comprising at least one of spatial data and spatio-temporal data stored therein and a control circuit that operably couples to that memory. The control circuit can be configured to access the data to be compressed in the memory and compress that data to provide compressed data. By one approach, the latter comprises subdividing the data to be compressed into a plurality of subspaces and then using an initialization scheme to construct at least one compressed representation of the data to be compressed.

公开(公告)号：US11722147B2

公开(公告)日：2023-08-08

申请号：US17583499

申请日：2022-01-25

申请人： Microsoft Technology Licensing, LLC

发明人： Kent D. Cedola ,  Larry Marvin Wall ,  Boris Bobrov ,  George Petre ,  Chad Balling McBride ,  Amol Ashok Ambardekar

IPC分类号： H03M7/30 ,  G06N3/04 ,  G06N3/063 ,  G06F12/0862 ,  G06F9/46 ,  G06F1/324 ,  G06F3/06 ,  G06F9/38 ,  G06F12/08 ,  G06F12/10 ,  G06F15/80 ,  G06F17/15 ,  G06N3/049 ,  G06N3/06 ,  G06N3/08 ,  G06N3/10 ,  H04L45/02 ,  H04L67/02 ,  G06F9/30 ,  H04L67/1001 ,  G06F9/48 ,  G06F12/02 ,  G06N3/045 ,  G06N3/065 ,  G06F13/16 ,  G06F1/3234 ,  G06F13/28 ,  H03M7/46 ,  H04L45/50

CPC分类号： H03M7/3059 ,  G06F1/324 ,  G06F1/3275 ,  G06F3/0604 ,  G06F3/067 ,  G06F3/0631 ,  G06F9/30087 ,  G06F9/3836 ,  G06F9/3887 ,  G06F9/46 ,  G06F9/4881 ,  G06F12/0207 ,  G06F12/0238 ,  G06F12/08 ,  G06F12/0862 ,  G06F12/10 ,  G06F13/1673 ,  G06F13/1689 ,  G06F13/28 ,  G06F15/8007 ,  G06F17/15 ,  G06N3/04 ,  G06N3/045 ,  G06N3/049 ,  G06N3/06 ,  G06N3/063 ,  G06N3/065 ,  G06N3/08 ,  G06N3/10 ,  H03M7/6005 ,  H03M7/6011 ,  H03M7/70 ,  H04L45/04 ,  H04L67/02 ,  H04L67/1001 ,  G06F2209/484 ,  G06F2209/485 ,  G06F2212/657 ,  H03M7/46 ,  H04L45/50 ,  Y02D10/00

摘要： Optimized memory usage and management is crucial to the overall performance of a neural network (NN) or deep neural network (DNN) computing environment. Using various characteristics of the input data dimension, an apportionment sequence is calculated for the input data to be processed by the NN or DNN that optimizes the efficient use of the local and external memory components. The apportionment sequence can describe how to parcel the input data (and its associated processing parameters—e.g., processing weights) into one or more portions as well as how such portions of input data (and its associated processing parameters) are passed between the local memory, external memory, and processing unit components of the NN or DNN. Additionally, the apportionment sequence can include instructions to store generated output data in the local and/or external memory components so as to optimize the efficient use of the local and/or external memory components.

公开(公告)号：US11710031B2

公开(公告)日：2023-07-25

申请号：US16698164

申请日：2019-11-27

申请人： Cambricon Technologies Corporation Limited

发明人： Shaoli Liu ,  Xinkai Song ,  Bingrui Wang ,  Yao Zhang ,  Shuai Hu

IPC分类号： G06N3/063 ,  G06N3/08 ,  G06N3/04 ,  H03M7/30

CPC分类号： G06N3/063 ,  G06N3/04 ,  G06N3/08 ,  H03M7/70

摘要： The present disclosure provides an integrated circuit chip device and a related product. The integrated circuit chip device includes: a primary processing circuit and a plurality of basic processing circuits. The primary processing circuit or at least one of the plurality of basic processing circuits includes the compression mapping circuits configured to perform compression on each data of a neural network operation. The technical solution provided by the present disclosure has the advantages of a small amount of computations and low power consumption.

公开(公告)号：US11676431B2

公开(公告)日：2023-06-13

申请号：US17100623

申请日：2020-11-20

申请人： Micron Technology, Inc.

发明人： Gil Golov

IPC分类号： G07C5/08 ,  H03M7/30

CPC分类号： G07C5/085 ,  H03M7/30 ,  H03M7/70

摘要： An improved black box data recorder for use with autonomous driving vehicles (AVD). In one embodiment, two cyclic buffers are provided to record vehicle sensors data. A first cyclic buffer records raw vehicle sensor data on a volatile memory, while a second cyclic buffer records the same vehicle sensor data, as compressed data, on a non-volatile memory. In a case of a collision or near collision, in one embodiment the buffers are flushed into a non-volatile (NV) storage for retrieval. As long as there is no power interruption, the raw vehicle sensor data will be accessible from the NV storage. If a power interruption occurs, the raw vehicle sensor data held in the volatile memory of the first cyclic buffer will be lost and only the compressed form of the vehicle sensor data from the second cyclic buffer will survive and be accessible.

公开(公告)号：US20190253072A1

公开(公告)日：2019-08-15

申请号：US16315792

申请日：2017-07-06

申请人： KINEMATICSOUP TECHNOLOGIES INC.

发明人： Justin MCMICHAEL

IPC分类号： H03M7/30 ,  H03M7/40 ,  A63F13/30

CPC分类号： H03M7/70 ,  A63F13/30 ,  H03M7/14 ,  H03M7/30 ,  H03M7/3066 ,  H03M7/4031

摘要： The disclosure is directed at a method of data compression using inferred data. By determining the number of leading zeroes for each data structure, a general header presenting all leading zeros can be generated and use to compress the data.

公开(公告)号：US20190190538A1

公开(公告)日：2019-06-20

申请号：US15846110

申请日：2017-12-18

申请人： Facebook, Inc.

发明人： Jong Soo Park ,  Nadav Rotem ,  Mikhail Smelyanskiy ,  Abdulkadir Utku Diril

IPC分类号： H03M7/30 ,  G06N3/02

CPC分类号： H03M7/6011 ,  G06N3/02 ,  H03M7/70

摘要： A system may include a memory device that stores parameters of a layer of a neural network that have been compressed. The system may also include a special-purpose hardware processing unit programmed to, for the layer of the neural network: (1) receive the compressed parameters from the memory device, (2) decompress the compressed parameters, and (3) apply the decompressed parameters in an arithmetic operation of the layer of the neural network. Various other methods, systems, and accelerators are also disclosed.

公开(公告)号：US10062089B2

公开(公告)日：2018-08-28

申请号：US15449687

申请日：2017-03-03

申请人： Groupon, Inc.

发明人： Ricardo A. Zilleruelo-Ramos ,  Hernan Enrique Arroyo Garcia ,  Joe Frisbie ,  Gaston L'Huillier ,  Francisco Jose Larrain

IPC分类号： G06Q30/02 ,  G06F17/30 ,  H03M7/30

CPC分类号： G06Q30/0246 ,  G06F16/1744 ,  G06F16/2282 ,  G06F16/951 ,  G06F16/955 ,  H03M7/30 ,  H03M7/70

摘要： In general, embodiments of the present invention provide systems, methods and computer readable media for data record compression using graph-based techniques.