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CL2019002864A1 - Procesador de red neuronal que utiliza compresión y descompresión de datos de activación para reducir la utilización de ancho de banda de memoria. - Google Patents

Procesador de red neuronal que utiliza compresión y descompresión de datos de activación para reducir la utilización de ancho de banda de memoria.

Info

Publication number
CL2019002864A1
CL2019002864A1 CL2019002864A CL2019002864A CL2019002864A1 CL 2019002864 A1 CL2019002864 A1 CL 2019002864A1 CL 2019002864 A CL2019002864 A CL 2019002864A CL 2019002864 A CL2019002864 A CL 2019002864A CL 2019002864 A1 CL2019002864 A1 CL 2019002864A1
Authority
CL
Chile
Prior art keywords
data
dnn
fragment
decompression
zero
Prior art date
Application number
CL2019002864A
Other languages
English (en)
Inventor
Joseph Leon Corkery
Benjamin Eliot Lundell
Larry Marvin Wall
Chad Balling Mcbride
Amol Ashok Ambardekar
George Petre
Kent D Cedola
Boris Bobrov
Original Assignee
Microsoft Technology Licensing Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Microsoft Technology Licensing Llc filed Critical Microsoft Technology Licensing Llc
Publication of CL2019002864A1 publication Critical patent/CL2019002864A1/es

Links

Classifications

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Abstract

UN MÓDULO DE RED NEURONAL PROFUNDA (DNN, POR SUS SIGLAS EN INGLÉS) PUEDE COMPRIMIR Y DESCOMPRIMIR DATOS DE ACTIVACIÓN GENERADOS POR NEURONAS PARA REDUCIR LA UTILIZACIÓN DEL ANCHO DE BANDA DEL BUS DE MEMORIA. LA UNIDAD DE COMPRESIÓN PUEDE RECIBIR UN FRAGMENTO DE DATOS DESCOMPRIMIDO GENERADO POR UNA NEURONA EN EL MÓDULO DE DNN. LA UNIDAD DE COMPRESIÓN GENERA UNA PORCIÓN DE MÁSCARA Y UNA PORCIÓN DE DATOS DE UN FRAGMENTO DE SALIDA COMPRIMIDO. LA PORCIÓN DE MÁSCARA CODIFICA LA PRESENCIA Y UBICACIÓN DE LOS BYTES CERO Y DISTINTOS DE CERO EN EL FRAGMENTO DE DATOS DESCOMPRIMIDO. LA PORCIÓN DE DATOS ALMACENA BYTES DISTINTOS DE CERO TRUNCADOS DEL FRAGMENTO DE DATOS DESCOMPRIMIDO. UNA UNIDAD DE DESCOMPRESIÓN PUEDE RECIBIR UN FRAGMENTO DE DATOS COMPRIMIDO DE LA MEMORIA EN EL PROCESADOR DE DNN O LA MEMORIA DE UN SERVIDOR DE APLICACIÓN. LA UNIDAD DE DESCOMPRESIÓN DESCOMPRIME EL FRAGMENTO DE DATOS COMPRIMIDO UTILIZANDO LA PORCIÓN DE MÁSCARA Y LA PORCIÓN DE DATOS. ESTO PUEDE REDUCIR LA UTILIZACIÓN DEL BUS DE MEMORIA, PERMITIR QUE UN MÓDULO DE DNN COMPLETE LAS OPERACIONES DE PROCESAMIENTO MÁS RÁPIDAMENTE Y REDUCIR EL CONSUMO DE ENERGÍA.
CL2019002864A 2017-04-17 2019-10-07 Procesador de red neuronal que utiliza compresión y descompresión de datos de activación para reducir la utilización de ancho de banda de memoria. CL2019002864A1 (es)

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Families Citing this family (147)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8515052B2 (en) 2007-12-17 2013-08-20 Wai Wu Parallel signal processing system and method
US10635969B2 (en) 2016-10-14 2020-04-28 International Business Machines Corporation Core utilization optimization by dividing computational blocks across cores
US10248906B2 (en) 2016-12-28 2019-04-02 Intel Corporation Neuromorphic circuits for storing and generating connectivity information
US10795836B2 (en) 2017-04-17 2020-10-06 Microsoft Technology Licensing, Llc Data processing performance enhancement for neural networks using a virtualized data iterator
US11164071B2 (en) * 2017-04-18 2021-11-02 Samsung Electronics Co., Ltd. Method and apparatus for reducing computational complexity of convolutional neural networks
WO2018214913A1 (zh) * 2017-05-23 2018-11-29 上海寒武纪信息科技有限公司 处理方法及加速装置
CN110502330A (zh) * 2018-05-16 2019-11-26 上海寒武纪信息科技有限公司 处理器及处理方法
US11514355B2 (en) * 2017-06-28 2022-11-29 General Electric Company Flat representation of machine learning model
WO2019095873A1 (zh) * 2017-11-20 2019-05-23 上海寒武纪信息科技有限公司 任务并行处理方法、装置、系统、存储介质及计算机设备
EP3489865B1 (en) * 2017-11-22 2021-01-06 Commissariat à l'énergie atomique et aux énergies alternatives A stdp-based learning method for a network having dual accumulator neurons
US10747844B2 (en) * 2017-12-12 2020-08-18 Tesla, Inc. Systems and methods for converting a matrix input to a vectorized input for a matrix processor
US11995448B1 (en) * 2018-02-08 2024-05-28 Marvell Asia Pte Ltd Method and apparatus for performing machine learning operations in parallel on machine learning hardware
US10970080B2 (en) 2018-02-08 2021-04-06 Marvell Asia Pte, Ltd. Systems and methods for programmable hardware architecture for machine learning
US12112175B1 (en) 2018-02-08 2024-10-08 Marvell Asia Pte Ltd Method and apparatus for performing machine learning operations in parallel on machine learning hardware
KR20190097930A (ko) * 2018-02-13 2019-08-21 삼성전자주식회사 채널 별 메모리 용량을 조절하는 메모리 장치 및 이를 포함하는 메모리 시스템
US10948966B1 (en) * 2018-03-07 2021-03-16 Facebook, Inc. Systems and methods for optimizing power usage for systems within quality-of-service constraints
US11126362B2 (en) * 2018-03-14 2021-09-21 International Business Machines Corporation Migrating storage data
WO2019200545A1 (zh) * 2018-04-17 2019-10-24 深圳鲲云信息科技有限公司 网络模型的运行方法及相关产品
US10404276B1 (en) * 2018-04-27 2019-09-03 Nicira, Inc. Stable variable-length order-preserving encoding scheme
US12282838B2 (en) * 2018-05-04 2025-04-22 Apple Inc. Systems and methods for assigning tasks in a neural network processor
US10997510B1 (en) 2018-05-22 2021-05-04 Marvell Asia Pte, Ltd. Architecture to support tanh and sigmoid operations for inference acceleration in machine learning
US11016801B1 (en) 2018-05-22 2021-05-25 Marvell Asia Pte, Ltd. Architecture to support color scheme-based synchronization for machine learning
US10360654B1 (en) * 2018-05-25 2019-07-23 Intel Corporation Software scoreboard information and synchronization
US10657087B2 (en) * 2018-05-31 2020-05-19 Toshiba Memory Corporation Method of out of order processing of scatter gather lists
US11561833B1 (en) * 2018-06-28 2023-01-24 Amazon Technologies, Inc. Allocation and placement of resources for network computation
WO2020032816A1 (en) * 2018-08-09 2020-02-13 Huawei Technologies Co., Ltd Device and method for compacting compressed and uncompressed data blocks
US12020146B2 (en) 2018-08-23 2024-06-25 Samsung Electronics Co., Ltd. Electronic device and operating method thereof of processing neural network model by using plurality of processors
JP6867518B2 (ja) * 2018-08-28 2021-04-28 カンブリコン テクノロジーズ コーポレイション リミティド データ前処理方法、装置、コンピュータ機器及び記憶媒体
KR102731057B1 (ko) * 2018-09-21 2024-11-15 삼성전자주식회사 메모리 장치와 통신하는 데이터 처리 장치 및 방법
US11295205B2 (en) * 2018-09-28 2022-04-05 Qualcomm Incorporated Neural processing unit (NPU) direct memory access (NDMA) memory bandwidth optimization
CN109359732B (zh) 2018-09-30 2020-06-09 阿里巴巴集团控股有限公司 一种芯片及基于其的数据处理方法
CN116541647A (zh) * 2018-10-09 2023-08-04 华为技术有限公司 运算加速器、处理方法及相关设备
US12182687B2 (en) * 2018-10-11 2024-12-31 International Business Machines Corporation Data representation for dynamic precision in neural network cores
JP7012168B2 (ja) * 2018-10-12 2022-01-27 オリンパス株式会社 演算処理装置
KR102720879B1 (ko) * 2018-11-05 2024-10-24 한국전자통신연구원 신경망 제어 장치 및 방법
KR102746521B1 (ko) * 2018-11-09 2024-12-23 삼성전자주식회사 뉴럴 프로세싱 유닛, 뉴럴 프로세싱 시스템, 및 어플리케이션 시스템
CN109669774B (zh) * 2018-11-14 2020-12-08 新华三技术有限公司成都分公司 硬件资源的量化方法、编排方法、装置及网络设备
US11663001B2 (en) * 2018-11-19 2023-05-30 Advanced Micro Devices, Inc. Family of lossy sparse load SIMD instructions
KR102107077B1 (ko) * 2018-11-20 2020-05-06 주식회사 아나패스 컨볼루션 신경망 추론에서 컨볼루션 연산을 수행하기 위한 라인 단위 메모리 관리 방법 및 그 추론 장치
US12499353B1 (en) * 2018-12-12 2025-12-16 Amazon Technologies, Inc. Configurable function approximation based on hardware selection of mapping table content
US10990525B2 (en) * 2018-12-12 2021-04-27 Mipsology SAS Caching data in artificial neural network computations
US11342933B2 (en) * 2018-12-14 2022-05-24 Advanced Micro Devices, Inc. Lossy significance compression with lossy restoration
CN109657788A (zh) * 2018-12-18 2019-04-19 北京中科寒武纪科技有限公司 数据处理方法、装置及相关产品
CN109740735B (zh) * 2018-12-29 2020-12-29 百度在线网络技术（北京）有限公司 多神经网络输出方法及装置、服务器、计算机可读介质
CN109922007B (zh) * 2019-01-15 2022-04-01 西安仙农电子科技有限公司 一种基于卷积神经网络的负载均衡方法
CN111488114B (zh) * 2019-01-28 2021-12-21 北京灵汐科技有限公司 一种可重构的处理器架构及计算设备
US11625554B2 (en) 2019-02-04 2023-04-11 International Business Machines Corporation L2-nonexpansive neural networks
US11521014B2 (en) 2019-02-04 2022-12-06 International Business Machines Corporation L2-nonexpansive neural networks
US11687783B2 (en) * 2019-02-04 2023-06-27 International Business Machines Corporation L2-nonexpansive neural networks
US11036545B2 (en) * 2019-03-15 2021-06-15 Intel Corporation Graphics systems and methods for accelerating synchronization using fine grain dependency check and scheduling optimizations based on available shared memory space
CN111767078B (zh) * 2019-04-02 2024-08-06 上海寒武纪信息科技有限公司 数据运行方法、装置和相关产品
CN109992225B (zh) * 2019-04-04 2022-02-22 中科寒武纪科技股份有限公司 数据输出方法及相关装置
CN111782577B (zh) 2019-04-04 2023-03-24 安徽寒武纪信息科技有限公司 数据处理装置及方法以及相关产品
KR102767856B1 (ko) * 2019-04-09 2025-02-17 한국전자통신연구원 정보 처리 장치 및 그것에 포함된 신경망 연산 장치의 동작 방법
US10504005B1 (en) * 2019-05-10 2019-12-10 Capital One Services, Llc Techniques to embed a data object into a multidimensional frame
KR102749978B1 (ko) 2019-05-10 2025-01-03 삼성전자주식회사 피처맵 데이터에 대한 압축을 수행하는 뉴럴 네트워크 프로세서 및 이를 포함하는 컴퓨팅 시스템
US11204745B2 (en) * 2019-05-23 2021-12-21 Xilinx, Inc. Dataflow graph programming environment for a heterogenous processing system
US11175898B2 (en) * 2019-05-31 2021-11-16 Apple Inc. Compiling code for a machine learning model for execution on a specialized processor
KR102774094B1 (ko) 2019-06-05 2025-03-04 삼성전자주식회사 전자 장치 및 그의 연산 수행 방법
US11556798B2 (en) * 2019-06-18 2023-01-17 Qualcomm Incorporated Optimizing machine learning model performance
US11403097B2 (en) 2019-06-26 2022-08-02 Intel Corporation Systems and methods to skip inconsequential matrix operations
US11461622B2 (en) * 2019-06-28 2022-10-04 Amazon Technologies, Inc. Dynamic code loading for multiple executions on a sequential processor
US11630770B2 (en) * 2019-07-11 2023-04-18 Meta Platforms Technologies, Llc Systems and methods for reading and writing sparse data in a neural network accelerator
US20210081806A1 (en) * 2019-09-13 2021-03-18 Latent AI, Inc. Using a runtime engine to facilitate dynamic adaptation of deep neural networks for efficient processing
US10915811B1 (en) 2019-09-18 2021-02-09 International Business Machines Corporation Intercalation cells for multi-task learning
US11475283B2 (en) * 2019-10-24 2022-10-18 Apple Inc. Multi dimensional convolution in neural network processor
KR102798811B1 (ko) 2019-11-01 2025-04-23 삼성전자주식회사 스토리지 장치 및 스토리지 장치의 동작 방법
US11513799B2 (en) 2019-11-04 2022-11-29 Apple Inc. Chained buffers in neural network processor
KR102817185B1 (ko) * 2019-11-27 2025-06-09 한국전자통신연구원 선인출 정보를 이용한 메모리 제어 방법 및 장치
KR102800488B1 (ko) 2019-12-06 2025-04-25 삼성전자주식회사 연산 장치, 그것의 동작 방법 및 뉴럴 네트워크 프로세서
WO2021126194A1 (en) * 2019-12-18 2021-06-24 Google Llc Parameter caching for neural network accelerators
CN111091184B (zh) * 2019-12-19 2022-03-22 浪潮(北京)电子信息产业有限公司 一种深度神经网络的量化方法、装置、电子设备及介质
CN111162792A (zh) * 2019-12-19 2020-05-15 深圳市航天泰瑞捷电子有限公司 一种电力负荷数据的压缩方法及装置
US11620516B2 (en) * 2019-12-23 2023-04-04 Arm Limited Specializing neural networks for heterogeneous systems
CN111126589B (zh) * 2019-12-31 2022-05-20 昆仑芯(北京)科技有限公司 神经网络数据处理装置、方法和电子设备
CN111178490B (zh) 2019-12-31 2021-08-24 北京百度网讯科技有限公司 数据输出方法、获取方法、装置和电子设备
KR102399197B1 (ko) 2020-01-17 2022-05-18 경희대학교 산학협력단 이상치 인지 근사적 코딩을 수행하는 전자 장치 그리고 그것의 동작 방법
US11023400B1 (en) 2020-01-20 2021-06-01 International Business Machines Corporation High performance DMA transfers in host bus adapters
US12072806B2 (en) * 2020-01-22 2024-08-27 Alibaba Group Holding Limited Compression and decompression module in a cache controller for reducing off-chip data traffic
KR102498066B1 (ko) * 2020-02-20 2023-02-10 한국과학기술원 딥러닝 강화학습 가속기
KR102860332B1 (ko) 2020-02-26 2025-09-16 삼성전자주식회사 가속기, 가속기의 동작 방법 및 이를 포함한 가속기 시스템
CN111431539B (zh) * 2020-03-04 2023-12-08 嘉楠明芯(北京)科技有限公司 一种神经网络数据的压缩方法、装置及计算机可读存储介质
CN111290979B (zh) * 2020-03-23 2021-08-17 优刻得科技股份有限公司 数据传输方法、装置及系统
WO2021203437A1 (zh) * 2020-04-10 2021-10-14 Oppo广东移动通信有限公司 资源配置方法、装置、设备及存储介质
CN111522643B (zh) * 2020-04-22 2024-06-25 杭州迪普科技股份有限公司 基于fpga的多队列调度方法、装置、计算机设备及存储介质
CN113592082B (zh) * 2020-04-30 2025-04-18 意法半导体股份有限公司 用于从人工神经网络分配中间数据的设备和方法
KR20210136476A (ko) * 2020-05-07 2021-11-17 삼성전자주식회사 쿼드 트리 방법의 파라미터들을 이용하여 압축하는 장치 및 방법
US11362672B2 (en) 2020-05-08 2022-06-14 Qualcomm Incorporated Inline decompression
US11494634B2 (en) * 2020-05-13 2022-11-08 International Business Machines Corporation Optimizing capacity and learning of weighted real-valued logic
US12015526B2 (en) * 2020-05-26 2024-06-18 Synopsys, Inc. Mixed-precision neural networks
GB202008299D0 (en) 2020-06-02 2020-07-15 Imagination Tech Ltd Manipulation of data in a memory
WO2021254856A1 (en) * 2020-06-18 2021-12-23 Interdigital Vc Holdings France, Sas Systems and methods for encoding/decoding a deep neural network
CN111753994B (zh) * 2020-06-22 2023-11-03 深圳鲲云信息科技有限公司 Ai芯片的数据处理方法、装置和计算机设备
CN111723053A (zh) * 2020-06-24 2020-09-29 北京航天数据股份有限公司 一种数据的压缩方法及装置、解压方法及装置
US11275701B2 (en) * 2020-06-24 2022-03-15 Qualcomm Incorporated Secure timer synchronization between function block and external SOC
US12197926B2 (en) * 2020-07-03 2025-01-14 Mediatek Inc. Dynamic loading neural network inference at DRAM/on-bus SRAM/serial flash for power optimization
CN111884658B (zh) * 2020-07-09 2025-05-20 格兰菲智能科技股份有限公司 数据解压缩方法、数据压缩方法及卷积运算装置
US11720404B2 (en) * 2020-07-16 2023-08-08 Samsung Electronics Co., Ltd. Systems and methods for arbitrating access to a shared resource
US20230267310A1 (en) * 2020-07-17 2023-08-24 Sony Group Corporation Neural network processing apparatus, information processing apparatus, information processing system, electronic device, neural network processing method, and program
CN111858058A (zh) * 2020-07-24 2020-10-30 成都成信高科信息技术有限公司 基于并行计算的sgd负载均衡方法、装置及存储介质
FR3113158B1 (fr) * 2020-08-03 2024-04-05 Commissariat Energie Atomique Architecture de calcul systolique pour la mise en œuvre de réseaux de neurones artificiels traitant plusieurs types de convolutions
CN114077889A (zh) * 2020-08-13 2022-02-22 华为技术有限公司 一种神经网络处理器和数据处理方法
US12493554B2 (en) 2020-09-09 2025-12-09 Ascenium, Inc. Parallel processing using hazard detection and mitigation
JP6835285B1 (ja) * 2020-09-15 2021-02-24 富士電機株式会社 データ圧縮方法、データ圧縮装置、データ圧縮プログラム、データ伸長方法、データ伸長装置およびデータ伸長プログラム
US11470004B2 (en) * 2020-09-22 2022-10-11 Advanced Micro Devices, Inc. Graded throttling for network-on-chip traffic
US12113712B2 (en) 2020-09-25 2024-10-08 Advanced Micro Devices, Inc. Dynamic network-on-chip throttling
US20220121937A1 (en) * 2020-10-21 2022-04-21 Samsung Electronics Co., Ltd. System and method for dynamic quantization for deep neural network feature maps
US11362670B2 (en) * 2020-10-30 2022-06-14 International Business Machines Corporation ReLU compression to reduce GPU memory
US11972137B2 (en) * 2020-11-02 2024-04-30 Deepx Co., Ltd. System and memory for artificial neural network (ANN) optimization using ANN data locality
US11922051B2 (en) 2020-11-02 2024-03-05 Deepx Co., Ltd. Memory controller, processor and system for artificial neural network
US12235778B2 (en) 2020-11-02 2025-02-25 Deepx Co., Ltd. Memory system of artificial neural network based on artificial neural network data locality
JP2022094508A (ja) 2020-12-15 2022-06-27 富士通株式会社 演算処理装置、演算処理方法および演算処理プログラム
US12210959B2 (en) * 2021-01-22 2025-01-28 Apple Inc. Branching operation for neural processor circuit
TWI745227B (zh) * 2021-02-01 2021-11-01 國立陽明交通大學 用於進行原始服務端與外地服務端之間的第三方認證的通訊系統及方法
KR102298766B1 (ko) * 2021-02-15 2021-09-07 주식회사 딥이티 타겟 디바이스에 대한 딥러닝 모델 변환 장치 및 방법
US11539936B2 (en) * 2021-03-25 2022-12-27 H3D, Inc. Imaging system for three-dimensional source localization
US12481867B2 (en) * 2021-04-28 2025-11-25 Arm Limited Memory for artificial neural network accelerator
US20220383121A1 (en) * 2021-05-25 2022-12-01 Applied Materials, Inc. Dynamic activation sparsity in neural networks
US11256987B1 (en) * 2021-06-02 2022-02-22 SambaNova Systems, Inc. Memory efficient dropout, with reordering of dropout mask elements
JP7684127B2 (ja) * 2021-07-26 2025-05-27 株式会社Preferred Networks データ処理方法、データ処理装置、データ処理プログラムおよびニューラルネットワークモデルの生成方法
JP2023018365A (ja) 2021-07-27 2023-02-08 富士通株式会社 情報処理プログラム、情報処理方法及び情報処理装置
US12307294B2 (en) * 2021-08-18 2025-05-20 Cisco Technology, Inc. Partitioning and placement of models of models at a network edge
CA3172010A1 (en) * 2021-09-01 2023-03-01 Royal Bank Of Canada Machine learning architecture for quantifying and monitoring event-based risk
US20230079975A1 (en) * 2021-09-10 2023-03-16 Arm Limited Power management for system-on-chip
US12112200B2 (en) 2021-09-13 2024-10-08 International Business Machines Corporation Pipeline parallel computing using extended memory
EP4429240A4 (en) * 2021-11-01 2025-10-29 Lg Electronics Inc METHOD AND APPARATUS FOR ENCODING/DECODING FEATURES AND RECORDING MEDIUM STORING A BINARY STREAM
KR102700292B1 (ko) * 2021-11-26 2024-08-29 건국대학교 산학협력단 신경망 가속기의 통신 특성을 동적으로 재구성하는 프로세서 장치, 및 그의 구동 방법
EP4191476A1 (en) * 2021-12-01 2023-06-07 Nokia Technologies Oy Machine learning accelerator
US11816364B2 (en) * 2022-01-13 2023-11-14 Microsoft Technology Licensing, Llc Performance evaluation of an application based on detecting degradation caused by other computing processes
CN114466082B (zh) * 2022-01-29 2024-01-09 上海阵量智能科技有限公司 数据压缩、数据解压方法、系统及人工智能ai芯片
US11720252B1 (en) * 2022-03-04 2023-08-08 Microsoft Technology Licensing, Llc Method and apparatus for compressing and decompressing sparse data sets
CN114879961B (zh) * 2022-04-20 2025-03-21 远光软件股份有限公司 一种组件渲染方法、装置以及计算机可读存储介质
US12159140B2 (en) * 2022-04-28 2024-12-03 Qualcomm Incorporated Instruction set architecture for neural network quantization and packing
US20250371319A1 (en) * 2022-06-22 2025-12-04 Brainchip, Inc. Method and system for implementing temporal convolution in spatiotemporal neural networks
KR20240002346A (ko) * 2022-06-29 2024-01-05 삼성전자주식회사 Ai 부호화/복호화를 이용하여 영상을 처리하는 전자 장치 및 그 제어 방법
KR102831394B1 (ko) * 2022-07-08 2025-07-08 리벨리온 주식회사 뉴럴 코어, 이를 포함하는 뉴럴 프로세싱 장치 및 뉴럴 프로세싱 장치의 데이터 로드 방법
CN115309349B (zh) 2022-10-12 2023-01-20 深圳鲲云信息科技有限公司 深度学习的稀疏数据存储方法、计算机设备和存储介质
EP4361809A1 (en) * 2022-10-31 2024-05-01 Tata Consultancy Services Limited Method and system for data regulations-aware cloud storage and processing service allocation
US11983128B1 (en) * 2022-12-16 2024-05-14 Amazon Technologies, Inc. Multidimensional and multiblock tensorized direct memory access descriptors
WO2024151267A1 (en) * 2023-01-13 2024-07-18 Google Llc Reducing leakage power of volatile memory
KR102849399B1 (ko) * 2023-03-30 2025-08-22 리벨리온 주식회사 뉴럴 프로세싱 장치, 뉴럴 프로세싱 시스템 및 뉴럴 프로세싱 장치의 커맨드 분기 처리 방법
TWI863496B (zh) * 2023-08-09 2024-11-21 新唐科技股份有限公司 控制晶片及開發板
US12487747B2 (en) * 2023-08-30 2025-12-02 Dell Products L.P. Padding synchronous write data with background write data based on storage system boundary alignment and size data
US12132502B1 (en) * 2023-10-09 2024-10-29 Qualcomm Incorporated Packet-based universal bit-field masking coding using configurable sparsity information
CN117579570B (zh) * 2023-11-29 2025-10-21 中科驭数（北京）科技有限公司 一种基于PCIe的数据传输方法、装置和系统
US12417386B2 (en) * 2023-12-12 2025-09-16 AtomBeam Technologies Inc. System and methods for upsampling of decompressed genomic data after lossy compression using a neural network
US12506496B2 (en) * 2024-05-23 2025-12-23 AtomBeam Technologies Inc. Hierarchical smart caching for machine learning codeword responses

Family Cites Families (195)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4298954A (en) 1979-04-30 1981-11-03 International Business Machines Corporation Alternating data buffers when one buffer is empty and another buffer is variably full of data
JPH0642237B2 (ja) 1983-12-28 1994-06-01 株式会社日立製作所 並列処理装置
EP0340901A3 (en) * 1988-03-23 1992-12-30 Du Pont Pixel Systems Limited Access system for dual port memory
US5056015A (en) * 1988-03-23 1991-10-08 Du Pont Pixel Systems Limited Architectures for serial or parallel loading of writable control store
EP0334624A3 (en) * 1988-03-23 1993-03-31 Du Pont Pixel Systems Limited Microcoded computer system
JP2703010B2 (ja) 1988-12-23 1998-01-26 株式会社日立製作所 ニユーラルネツト信号処理プロセツサ
US5369773A (en) 1991-04-26 1994-11-29 Adaptive Solutions, Inc. Neural network using virtual-zero
US5357597A (en) * 1991-06-24 1994-10-18 International Business Machines Corporation Convolutional expert neural system (ConExNS)
US5487153A (en) 1991-08-30 1996-01-23 Adaptive Solutions, Inc. Neural network sequencer and interface apparatus
WO1993014459A1 (en) 1992-01-17 1993-07-22 Caelum Research Corporation Modular parallel processing system
JPH06195322A (ja) 1992-10-29 1994-07-15 Hitachi Ltd 汎用型ニューロコンピュータとして用いられる情報処理装置
JP2938711B2 (ja) 1993-05-10 1999-08-25 松下電器産業株式会社 並列計算機
US5859990A (en) 1995-12-29 1999-01-12 Intel Corporation System for transferring data segments from a first storage device to a second storage device using an alignment stage including even and odd temporary devices
US5933654A (en) 1996-09-24 1999-08-03 Allen-Bradley Company, Llc Dynamic buffer fracturing by a DMA controller
US6006325A (en) * 1996-12-19 1999-12-21 Institute For The Development Of Emerging Architectures, L.L.C. Method and apparatus for instruction and data serialization in a computer processor
US6547364B2 (en) * 1997-07-12 2003-04-15 Silverbrook Research Pty Ltd Printing cartridge with an integrated circuit device
KR100258355B1 (ko) * 1997-12-26 2000-06-01 김영환 8 비트 병렬 셀 단위 인터리버
US6307867B1 (en) 1998-05-14 2001-10-23 Telefonaktiebolaget Lm Ericsson (Publ) Data transmission over a communications link with variable transmission rates
US6654761B2 (en) * 1998-07-29 2003-11-25 Inxight Software, Inc. Controlling which part of data defining a node-link structure is in memory
JP2000059227A (ja) 1998-08-07 2000-02-25 Matsushita Electric Ind Co Ltd 符号化／復号化装置、及び符号化／復号化方法
JP2000261416A (ja) * 1999-03-09 2000-09-22 Nec Eng Ltd 二重化データ転送回路
US6785239B1 (en) 1999-06-01 2004-08-31 Cisco Technology, Inc. Reducing delays in a communication network using a re-fragmentation pipeline
JP2001188767A (ja) 1999-12-28 2001-07-10 Fuji Xerox Co Ltd ニューラルネットワーク演算装置及びニューラルネットワークの演算方法
US6424737B1 (en) 2000-01-24 2002-07-23 Sony Corporation Method and apparatus of compressing images using localized radon transforms
US6988154B2 (en) 2000-03-10 2006-01-17 Arc International Memory interface and method of interfacing between functional entities
GB2382899B (en) 2000-12-29 2003-12-17 Zarlink Semiconductor Ltd A data queue system
JP2002259939A (ja) * 2001-03-05 2002-09-13 Kitakiyuushiyuu Techno Center:Kk 連想メモリーベースコンピュータ
US6990079B2 (en) 2001-06-08 2006-01-24 International Business Machines Corporation Optimizing fragment sizes in frame relay networks
US7012893B2 (en) 2001-06-12 2006-03-14 Smartpackets, Inc. Adaptive control of data packet size in networks
US7106968B2 (en) 2001-07-06 2006-09-12 Optix Networks Inc. Combined SONET/SDH and OTN architecture
US6954744B2 (en) * 2001-08-29 2005-10-11 Honeywell International, Inc. Combinatorial approach for supervised neural network learning
US6836767B2 (en) 2001-10-03 2004-12-28 International Business Machines Corporation Pipelined hardware implementation of a neural network circuit
US6961719B1 (en) * 2002-01-07 2005-11-01 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Hybrid neural network and support vector machine method for optimization
US7245627B2 (en) 2002-04-23 2007-07-17 Mellanox Technologies Ltd. Sharing a network interface card among multiple hosts
US7539608B1 (en) 2002-05-10 2009-05-26 Oracle International Corporation Techniques for determining effects on system performance of a memory management parameter
US7020207B1 (en) * 2002-12-02 2006-03-28 Hitachi, Ltd. Video error concealment mechanism for block based video decompression
US7444637B2 (en) 2003-02-18 2008-10-28 Microsoft Corporation Systems and methods for scheduling coprocessor resources in a computing system
US7137021B2 (en) * 2003-05-15 2006-11-14 International Business Machines Corporation Power saving in FPU with gated power based on opcodes and data
GB0313986D0 (en) * 2003-06-17 2003-07-23 Zarlink Semiconductor Inc Data memory extension for use in double buffered TDM switches
JP4452690B2 (ja) 2003-12-09 2010-04-21 パナソニック株式会社 電子装置、その制御方法、ホスト装置及びその制御方法
US20050125797A1 (en) * 2003-12-09 2005-06-09 International Business Machines Corporation Resource management for a system-on-chip (SoC)
US7480640B1 (en) * 2003-12-16 2009-01-20 Quantum Leap Research, Inc. Automated method and system for generating models from data
US7376853B2 (en) 2004-03-15 2008-05-20 Canon Kabushiki Kaisha Network apparatus, method for controlling the same, and program for the same
US7284075B2 (en) 2004-03-23 2007-10-16 Intel Corporation Inbound packet placement in host memory
US7644239B2 (en) * 2004-05-03 2010-01-05 Microsoft Corporation Non-volatile memory cache performance improvement
US9143393B1 (en) * 2004-05-25 2015-09-22 Red Lambda, Inc. System, method and apparatus for classifying digital data
US20050289253A1 (en) * 2004-06-24 2005-12-29 Edirisooriya Samantha J Apparatus and method for a multi-function direct memory access core
US7363397B2 (en) 2004-08-26 2008-04-22 International Business Machines Corporation System and method for DMA controller with multi-dimensional line-walking functionality
US20060050693A1 (en) * 2004-09-03 2006-03-09 James Bury Building data packets for an advanced switching fabric
US20060100997A1 (en) * 2004-10-27 2006-05-11 Wall Gary C Data caching
US8190796B2 (en) * 2004-11-02 2012-05-29 Standard Microsystems Corporation Hardware supported peripheral component memory alignment method
CN1790918A (zh) 2004-12-17 2006-06-21 中国科学院半导体研究所 基于虚拟信源和神经网络的无损数据压缩方法
US20060143401A1 (en) * 2004-12-27 2006-06-29 Jacob Doweck Method and apparatus for prefetching based on cache fill buffer hits
EP1701249A1 (en) * 2005-03-11 2006-09-13 Interuniversitair Microelektronica Centrum Vzw Ultra low power ASIP (Application-Domain specific Instruction-set Processor) microcomputer
US7793040B2 (en) * 2005-06-01 2010-09-07 Microsoft Corporation Content addressable memory architecture
US7747070B2 (en) * 2005-08-31 2010-06-29 Microsoft Corporation Training convolutional neural networks on graphics processing units
CN101401100B (zh) * 2006-03-14 2012-10-10 国际商业机器公司 通过确定输入数据中的模式进行数据挖掘
US8139593B2 (en) * 2006-03-31 2012-03-20 Qualcomm Incorporated Memory management for high speed media access control
US9542642B2 (en) 2006-04-06 2017-01-10 Samuel F. Wood Packet data neural network system and method
US7764710B1 (en) * 2006-04-25 2010-07-27 Altera Corporation Method and apparatus for processing communication protocol frame input
US7620784B2 (en) * 2006-06-09 2009-11-17 Microsoft Corporation High speed nonvolatile memory device using parallel writing among a plurality of interfaces
US8718065B2 (en) 2006-08-15 2014-05-06 Broadcom Corporation Transmission using multiple physical interface
US7496707B2 (en) 2006-08-22 2009-02-24 International Business Machines Corporation Dynamically scalable queues for performance driven PCI express memory traffic
US20080091868A1 (en) * 2006-10-17 2008-04-17 Shay Mizrachi Method and System for Delayed Completion Coalescing
US8249171B2 (en) 2006-11-10 2012-08-21 Texas Instruments Incorporated MPEG-2 transport stream packet synchronizer
US20080168013A1 (en) * 2006-12-05 2008-07-10 Paul Cadaret Scalable pattern recognition system
CN101690068A (zh) * 2006-12-06 2010-03-31 弗森多系统公司（dba弗森-艾奥） 用于在多个独立主机之间共享的设备的装置、系统、以及方法
EP2122542B1 (en) 2006-12-08 2017-11-01 Medhat Moussa Architecture, system and method for artificial neural network implementation
CN101221541B (zh) * 2007-01-09 2011-04-20 张立军 用于soc的可编程通信控制器
US7620749B2 (en) * 2007-01-10 2009-11-17 International Business Machines Corporation Descriptor prefetch mechanism for high latency and out of order DMA device
US8190834B2 (en) 2007-06-15 2012-05-29 Emc Corporation Process for contiguously streaming data from a content addressed storage system
JP5184824B2 (ja) * 2007-06-15 2013-04-17 キヤノン株式会社 演算処理装置及び方法
US7822951B2 (en) 2007-08-01 2010-10-26 Advanced Micro Devices, Inc. System and method of load-store forwarding
US8200992B2 (en) * 2007-09-24 2012-06-12 Cognitive Electronics, Inc. Parallel processing computer systems with reduced power consumption and methods for providing the same
CN101183873B (zh) 2007-12-11 2011-09-28 广州中珩电子科技有限公司 一种基于bp神经网络的嵌入式系统数据压缩解压缩方法
US8244953B1 (en) 2007-12-18 2012-08-14 Emc Corporation System and method for faster data retrieval from tape media
US8244721B2 (en) * 2008-02-13 2012-08-14 Microsoft Corporation Using related users data to enhance web search
US7730244B1 (en) * 2008-03-27 2010-06-01 Xilinx, Inc. Translation of commands in an interconnection of an embedded processor block core in an integrated circuit
US8201166B2 (en) * 2008-04-30 2012-06-12 Hewlett-Packard Development Company, L.P. Virtualization platform configured with virtual connect control
GB0811057D0 (en) 2008-06-17 2008-07-23 Univ Ulster Artificial neural network architecture
US8566515B2 (en) * 2009-01-12 2013-10-22 Maxim Integrated Products, Inc. Memory subsystem
US20100180100A1 (en) 2009-01-13 2010-07-15 Mavrix Technology, Inc. Matrix microprocessor and method of operation
US8392687B2 (en) * 2009-01-21 2013-03-05 Micron Technology, Inc. Solid state memory formatting
JP5458629B2 (ja) * 2009-03-31 2014-04-02 ブラザー工業株式会社 ノード装置、ノード処理プログラム及び検索方法
US20100257174A1 (en) 2009-04-02 2010-10-07 Matthew Dino Minuti Method for data compression utilizing pattern-analysis and matching means such as neural networks
US20100281192A1 (en) 2009-04-30 2010-11-04 Novafora, Inc. Apparatus and method for transferring data within a data processing system
EP2259214B1 (en) 2009-06-04 2013-02-27 Honda Research Institute Europe GmbH Implementing a neural associative memory based on non-linear learning of discrete synapses
WO2010151267A1 (en) * 2009-06-26 2010-12-29 Intel Corporation Optimizations for an unbounded transactional memory (utm) system
US8442927B2 (en) 2009-07-30 2013-05-14 Nec Laboratories America, Inc. Dynamically configurable, multi-ported co-processor for convolutional neural networks
US8316194B2 (en) * 2009-12-15 2012-11-20 Intel Corporation Mechanisms to accelerate transactions using buffered stores
US20110153877A1 (en) * 2009-12-23 2011-06-23 King Steven R Method and apparatus to exchange data via an intermediary translation and queue manager
WO2011085934A1 (en) * 2010-01-18 2011-07-21 Xelerated Ab A packet buffer comprising a data section and a data description section
US8713260B2 (en) 2010-04-02 2014-04-29 Intel Corporation Adaptive block pre-fetching method and system
US8549506B2 (en) * 2010-04-27 2013-10-01 Microsoft Corporation Resumable methods
US8965819B2 (en) * 2010-08-16 2015-02-24 Oracle International Corporation System and method for effective caching using neural networks
US8701099B2 (en) * 2010-11-02 2014-04-15 International Business Machines Corporation Accelerating generic loop iterators using speculative execution
US9300321B2 (en) * 2010-11-05 2016-03-29 University of Maribor Light detection and ranging (LiDAR)data compression and decompression methods and apparatus
US8515882B2 (en) 2010-11-18 2013-08-20 International Business Machines Corporation Efficient storage of individuals for optimization simulation
CN102480337B (zh) 2010-11-30 2016-04-13 国际商业机器公司 无线电软件系统以及用于其的解码装置和方法
US8966413B2 (en) * 2011-02-17 2015-02-24 The Board Of Trustees Of The Leland Stanford Junior University System and method for a chip generator
US8892488B2 (en) * 2011-06-01 2014-11-18 Nec Laboratories America, Inc. Document classification with weighted supervised n-gram embedding
US9288251B2 (en) * 2011-06-10 2016-03-15 Citrix Systems, Inc. Adaptive bitrate management on progressive download with indexed media files
CN102332162A (zh) 2011-09-19 2012-01-25 西安百利信息科技有限公司 基于人工神经网络的医学图像兴趣区自动识别和分级压缩方法
US9015092B2 (en) * 2012-06-04 2015-04-21 Brain Corporation Dynamically reconfigurable stochastic learning apparatus and methods
US9326075B2 (en) 2011-10-07 2016-04-26 Cochlear Limited Flexible protocol for an implanted prosthesis
US9235799B2 (en) * 2011-11-26 2016-01-12 Microsoft Technology Licensing, Llc Discriminative pretraining of deep neural networks
US9141166B2 (en) * 2011-12-13 2015-09-22 Intel Corporation Method, apparatus, and system for energy efficiency and energy conservation including dynamic control of energy consumption in power domains
CN102523452B (zh) 2011-12-29 2014-12-17 西安空间无线电技术研究所 图像转换压缩传输方法
CN102609222B (zh) * 2012-02-13 2015-03-25 山东华芯半导体有限公司 基于命令描述符的闪存控制方法
US9128925B2 (en) * 2012-04-24 2015-09-08 Freescale Semiconductor, Inc. System and method for direct memory access buffer utilization by setting DMA controller with plurality of arbitration weights associated with different DMA engines
US9509632B2 (en) * 2012-04-25 2016-11-29 Empire Technology Development Llc Workload prediction for network-based computing
US9703500B2 (en) * 2012-04-25 2017-07-11 International Business Machines Corporation Reducing power consumption by migration of data within a tiered storage system
US9015096B2 (en) * 2012-05-30 2015-04-21 Qualcomm Incorporated Continuous time spiking neural network event-based simulation that schedules co-pending events using an indexable list of nodes
US9432489B2 (en) * 2012-06-05 2016-08-30 Intel Corporation Systems and methods for processing encoded data streams
US9159020B2 (en) * 2012-09-14 2015-10-13 International Business Machines Corporation Multiplexing physical neurons to optimize power and area
US20160013773A1 (en) * 2012-11-06 2016-01-14 Pavel Dourbal Method and apparatus for fast digital filtering and signal processing
WO2014085975A1 (zh) * 2012-12-04 2014-06-12 中国科学院半导体研究所 可动态重构的多级并行单指令多数据阵列处理系统
KR20150064197A (ko) 2012-12-26 2015-06-10 인텔 코포레이션 인접한 수집/분산 연산들의 통합
EP2949047B1 (en) * 2013-01-22 2021-03-31 Altera Corporation Data compression and decompression using simd instructions
US10909137B2 (en) 2014-10-06 2021-02-02 Fisher-Rosemount Systems, Inc. Streaming data for analytics in process control systems
CN104050200B (zh) 2013-03-15 2017-12-08 伊姆西公司 用于数据拷贝的方法和装置
US9760346B2 (en) * 2013-05-31 2017-09-12 Microsoft Technology Licensing, Llc Deeply parallel source code compilation
WO2014204331A1 (en) 2013-06-17 2014-12-24 Llc "Topcon Positioning Systems" Nand flash memory interface controller with gnss receiver firmware booting capability
CA2924375A1 (en) * 2013-09-19 2015-03-26 Sysomos L.P. Systems and methods for actively composing content for use in continuous social communication
US9280465B2 (en) * 2013-10-08 2016-03-08 Globalfoundries Inc. Techniques for moving checkpoint-based high-availability log and data directly from a producer cache to a consumer cache
US20150286873A1 (en) * 2014-04-03 2015-10-08 Bruce L. Davis Smartphone-based methods and systems
US9286171B2 (en) * 2013-12-12 2016-03-15 International Business Machines Corporation Priming failover of stateful offload adapters
JP6273010B2 (ja) * 2013-12-23 2018-01-31 インテル コーポレイション 入出力データアライメント
GB2521828A (en) * 2013-12-23 2015-07-08 Sony Corp Data encoding and decoding
US9851771B2 (en) 2013-12-28 2017-12-26 Intel Corporation Dynamic power measurement and estimation to improve memory subsystem power performance
US10097372B2 (en) * 2014-01-09 2018-10-09 Ciena Corporation Method for resource optimized network virtualization overlay transport in virtualized data center environments
EP2896428B1 (fr) * 2014-01-16 2016-11-09 Sorin CRM SAS Ensemble de réseau de neurones pour l'évaluation et l'adaptation d'une thérapie antitachycardique par un défibrillateur implantable
US10339447B2 (en) * 2014-01-23 2019-07-02 Qualcomm Incorporated Configuring sparse neuronal networks
US9563369B2 (en) * 2014-04-14 2017-02-07 Microsoft Technology Licensing, Llc Fine-grained bandwidth provisioning in a memory controller
KR101925905B1 (ko) * 2014-04-15 2019-01-28 인텔 코포레이션 연상 메모리들을 사용하는 뉴로모픽 그래프 압축을 위한 방법들, 시스템들 및 컴퓨터 프로그램 제품들
US9219499B2 (en) 2014-05-16 2015-12-22 Robert Bosch Gmbh Run time compression method for a vehicle communication bus
US9892125B1 (en) * 2014-05-23 2018-02-13 MapD Technologies, Inc. Method for logging update queries
US9959142B2 (en) 2014-06-17 2018-05-01 Mediatek Inc. Dynamic task scheduling method for dispatching sub-tasks to computing devices of heterogeneous computing system and related computer readable medium
CN106170800A (zh) * 2014-09-12 2016-11-30 微软技术许可有限责任公司 经由输出分布来学习学生dnn
US9990307B1 (en) 2014-10-29 2018-06-05 Netronome Systems, Inc. Split packet transmission DMA engine
EP3035249B1 (en) 2014-12-19 2019-11-27 Intel Corporation Method and apparatus for distributed and cooperative computation in artificial neural networks
EP3035204B1 (en) 2014-12-19 2018-08-15 Intel Corporation Storage device and method for performing convolution operations
US10223635B2 (en) 2015-01-22 2019-03-05 Qualcomm Incorporated Model compression and fine-tuning
CN104573064B (zh) * 2015-01-23 2017-12-08 四川中科腾信科技有限公司 一种大数据环境下的数据处理方法
US10234930B2 (en) * 2015-02-13 2019-03-19 Intel Corporation Performing power management in a multicore processor
US20160267377A1 (en) * 2015-03-12 2016-09-15 Staples, Inc. Review Sentiment Analysis
WO2016149944A1 (zh) * 2015-03-26 2016-09-29 北京旷视科技有限公司 用于识别人脸的方法、系统和计算机程序产品
US9378044B1 (en) * 2015-03-28 2016-06-28 Vmware, Inc. Method and system that anticipates deleterious virtual-machine state changes within a virtualization layer
US9928144B2 (en) * 2015-03-30 2018-03-27 Commvault Systems, Inc. Storage management of data using an open-archive architecture, including streamlined access to primary data originally stored on network-attached storage and archived to secondary storage
FR3035243B1 (fr) * 2015-04-20 2018-06-29 Commissariat A L'energie Atomique Et Aux Energies Alternatives Placement d'une tache de calcul sur un processeur fonctionnellement asymetrique
US9965824B2 (en) * 2015-04-23 2018-05-08 Google Llc Architecture for high performance, power efficient, programmable image processing
US20160328644A1 (en) 2015-05-08 2016-11-10 Qualcomm Incorporated Adaptive selection of artificial neural networks
US20160335119A1 (en) 2015-05-12 2016-11-17 minds.ai inc Batch-based neural network system
US10083395B2 (en) * 2015-05-21 2018-09-25 Google Llc Batch processing in a neural network processor
US9595002B2 (en) * 2015-05-29 2017-03-14 Sas Institute Inc. Normalizing electronic communications using a vector having a repeating substring as input for a neural network
CN106203619B (zh) * 2015-05-29 2022-09-13 三星电子株式会社 数据优化的神经网络遍历
US20160350653A1 (en) * 2015-06-01 2016-12-01 Salesforce.Com, Inc. Dynamic Memory Network
US20160358069A1 (en) * 2015-06-03 2016-12-08 Samsung Electronics Co., Ltd. Neural network suppression
CN106250981B (zh) * 2015-06-10 2022-04-01 三星电子株式会社 减少存储器访问和网络内带宽消耗的脉冲神经网络
US10275001B2 (en) 2015-06-26 2019-04-30 Intel Corporation Thermal throttling of electronic devices
US20160378491A1 (en) 2015-06-26 2016-12-29 Microsoft Technology Licensing, Llc Determination of target location for transfer of processor control
US20160379109A1 (en) * 2015-06-29 2016-12-29 Microsoft Technology Licensing, Llc Convolutional neural networks on hardware accelerators
US11244225B2 (en) 2015-07-10 2022-02-08 Samsung Electronics Co., Ltd. Neural network processor configurable using macro instructions
CN108140131B (zh) 2015-10-04 2021-09-14 艾腾怀斯股份有限公司 用于将卷积网络应用于空间数据的系统和方法
US11029949B2 (en) * 2015-10-08 2021-06-08 Shanghai Zhaoxin Semiconductor Co., Ltd. Neural network unit
CN106445468B (zh) * 2015-10-08 2019-03-15 上海兆芯集成电路有限公司 利用处理器架构指令加载架构缓存器文件的微运算的执行单元的直接执行
US10471594B2 (en) * 2015-12-01 2019-11-12 Kindred Systems Inc. Systems, devices, and methods for the distribution and collection of multimodal data associated with robots
CN105488563A (zh) * 2015-12-16 2016-04-13 重庆大学 面向深度学习的稀疏自适应神经网络、算法及实现装置
US10007519B2 (en) * 2015-12-22 2018-06-26 Intel IP Corporation Instructions and logic for vector bit field compression and expansion
US11232085B2 (en) * 2016-01-07 2022-01-25 Amazon Technologies, Inc. Outlier detection for streaming data
CN107506828B (zh) * 2016-01-20 2020-11-03 中科寒武纪科技股份有限公司 用于稀疏连接的人工神经网络计算装置和方法
US10565207B2 (en) * 2016-04-12 2020-02-18 Hsilin Huang Method, system and program product for mask-based compression of a sparse matrix
CN106203624B (zh) * 2016-06-23 2019-06-21 上海交通大学 基于深度神经网络的矢量量化系统及方法
CN106204468B (zh) * 2016-06-27 2019-04-26 深圳市未来媒体技术研究院 一种基于ReLU卷积神经网络的图像去噪方法
US10528864B2 (en) * 2016-08-11 2020-01-07 Nvidia Corporation Sparse convolutional neural network accelerator
WO2018058452A1 (zh) * 2016-09-29 2018-04-05 北京中科寒武纪科技有限公司 一种执行人工神经网络运算的装置和方法
US10296292B2 (en) * 2016-10-20 2019-05-21 Advanced Micro Devices, Inc. Dynamic variable precision computation
CN106530200B (zh) 2016-10-23 2020-01-07 深圳大学 一种基于深度学习模型的隐写图像检测方法及系统
US9959498B1 (en) 2016-10-27 2018-05-01 Google Llc Neural network instruction set architecture
CN106529670B (zh) * 2016-10-27 2019-01-25 中国科学院计算技术研究所 一种基于权重压缩的神经网络处理器、设计方法、芯片
US10067710B2 (en) * 2016-11-23 2018-09-04 Advanced Micro Devices, Inc. Detecting buffer overflows in general-purpose GPU applications
US10037490B2 (en) * 2016-12-13 2018-07-31 Google Llc Performing average pooling in hardware
US20180164866A1 (en) * 2016-12-13 2018-06-14 Qualcomm Incorporated Low-power architecture for sparse neural network
US10169296B2 (en) * 2016-12-30 2019-01-01 Intel Corporation Distributed matrix multiplication for neural networks
US12073308B2 (en) 2017-01-04 2024-08-27 Stmicroelectronics International N.V. Hardware accelerator engine
US10096134B2 (en) * 2017-02-01 2018-10-09 Nvidia Corporation Data compaction and memory bandwidth reduction for sparse neural networks
US10333549B1 (en) * 2017-03-08 2019-06-25 iDensify LLC System and components for encoding integers
US10909447B2 (en) 2017-03-09 2021-02-02 Google Llc Transposing neural network matrices in hardware
US10795836B2 (en) 2017-04-17 2020-10-06 Microsoft Technology Licensing, Llc Data processing performance enhancement for neural networks using a virtualized data iterator
US10671349B2 (en) * 2017-07-24 2020-06-02 Tesla, Inc. Accelerated mathematical engine
US12346835B2 (en) * 2017-09-08 2025-07-01 Nvidia Corporation Data inspection for compression/decompression configuration and data type determination
KR20190066473A (ko) * 2017-12-05 2019-06-13 삼성전자주식회사 뉴럴 네트워크에서 컨볼루션 연산을 처리하는 방법 및 장치
US12014505B2 (en) * 2019-01-31 2024-06-18 Samsung Electronics Co., Ltd. Method and apparatus with convolution neural network processing using shared operand
US11671111B2 (en) * 2019-04-17 2023-06-06 Samsung Electronics Co., Ltd. Hardware channel-parallel data compression/decompression
CN112465129B (zh) * 2019-09-09 2024-01-09 上海登临科技有限公司 片内异构人工智能处理器

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