PL3579117T3 - Instrukcja mnożenia macierzy o zmiennym formacie i zmiennej rzadkości - Google Patents
Instrukcja mnożenia macierzy o zmiennym formacie i zmiennej rzadkościInfo
- Publication number
- PL3579117T3 PL3579117T3 PL19172622.3T PL19172622T PL3579117T3 PL 3579117 T3 PL3579117 T3 PL 3579117T3 PL 19172622 T PL19172622 T PL 19172622T PL 3579117 T3 PL3579117 T3 PL 3579117T3
- Authority
- PL
- Poland
- Prior art keywords
- variable
- sparseness
- format
- matrix multiplication
- multiplication instruction
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
- G06F9/3001—Arithmetic instructions
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
- G06F9/30036—Instructions to perform operations on packed data, e.g. vector, tile or matrix operations
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
- G06F7/38—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
- G06F7/48—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
- G06F7/52—Multiplying; Dividing
- G06F7/523—Multiplying only
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
- G06F9/30036—Instructions to perform operations on packed data, e.g. vector, tile or matrix operations
- G06F9/30038—Instructions to perform operations on packed data, e.g. vector, tile or matrix operations using a mask
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30145—Instruction analysis, e.g. decoding, instruction word fields
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30145—Instruction analysis, e.g. decoding, instruction word fields
- G06F9/3016—Decoding the operand specifier, e.g. specifier format
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Neurology (AREA)
- Computational Linguistics (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multi Processors (AREA)
- Complex Calculations (AREA)
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/003,545 US10599429B2 (en) | 2018-06-08 | 2018-06-08 | Variable format, variable sparsity matrix multiplication instruction |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| PL3579117T3 true PL3579117T3 (pl) | 2024-09-23 |
Family
ID=65229501
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PL19172622.3T PL3579117T3 (pl) | 2018-06-08 | 2019-05-03 | Instrukcja mnożenia macierzy o zmiennym formacie i zmiennej rzadkości |
Country Status (5)
| Country | Link |
|---|---|
| US (2) | US10599429B2 (pl) |
| EP (2) | EP3772000A1 (pl) |
| CN (3) | CN119166216A (pl) |
| ES (1) | ES2988859T3 (pl) |
| PL (1) | PL3579117T3 (pl) |
Families Citing this family (45)
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| WO2019090325A1 (en) | 2017-11-06 | 2019-05-09 | Neuralmagic, Inc. | Methods and systems for improved transforms in convolutional neural networks |
| US11715287B2 (en) | 2017-11-18 | 2023-08-01 | Neuralmagic Inc. | Systems and methods for exchange of data in distributed training of machine learning algorithms |
| US11216732B2 (en) | 2018-05-31 | 2022-01-04 | Neuralmagic Inc. | Systems and methods for generation of sparse code for convolutional neural networks |
| US10832133B2 (en) | 2018-05-31 | 2020-11-10 | Neuralmagic Inc. | System and method of executing neural networks |
| WO2021061172A1 (en) * | 2019-09-27 | 2021-04-01 | Neuralmagic Inc. | System and method of executing neural networks |
| US10963787B2 (en) | 2018-05-31 | 2021-03-30 | Neuralmagic Inc. | Systems and methods for generation of sparse code for convolutional neural networks |
| US11449363B2 (en) | 2018-05-31 | 2022-09-20 | Neuralmagic Inc. | Systems and methods for improved neural network execution |
| US11062232B2 (en) * | 2018-08-01 | 2021-07-13 | International Business Machines Corporation | Determining sectors of a track to stage into cache using a machine learning module |
| US11080622B2 (en) * | 2018-08-01 | 2021-08-03 | International Business Machines Corporation | Determining sectors of a track to stage into cache by training a machine learning module |
| WO2020046859A1 (en) | 2018-08-27 | 2020-03-05 | Neuralmagic Inc. | Systems and methods for neural network convolutional layer matrix multiplication using cache memory |
| US10719323B2 (en) | 2018-09-27 | 2020-07-21 | Intel Corporation | Systems and methods for performing matrix compress and decompress instructions |
| WO2020072274A1 (en) | 2018-10-01 | 2020-04-09 | Neuralmagic Inc. | Systems and methods for neural network pruning with accuracy preservation |
| US20200183837A1 (en) | 2018-12-07 | 2020-06-11 | Samsung Electronics Co., Ltd. | Dataflow accelerator architecture for general matrix-matrix multiplication and tensor computation in deep learning |
| US20200210517A1 (en) | 2018-12-27 | 2020-07-02 | Intel Corporation | Systems and methods to accelerate multiplication of sparse matrices |
| US11544559B2 (en) | 2019-01-08 | 2023-01-03 | Neuralmagic Inc. | System and method for executing convolution in a neural network |
| CN111596886B (zh) * | 2019-02-21 | 2026-01-16 | 超威半导体公司 | 混合矩阵乘法流水线 |
| CN111738429B (zh) * | 2019-03-25 | 2023-10-13 | 中科寒武纪科技股份有限公司 | 一种计算装置及相关产品 |
| US20200341772A1 (en) | 2019-04-29 | 2020-10-29 | DeGirum Corporation | Efficient Architectures For Deep Learning Algorithms |
| US11334647B2 (en) | 2019-06-29 | 2022-05-17 | Intel Corporation | Apparatuses, methods, and systems for enhanced matrix multiplier architecture |
| US11195095B2 (en) | 2019-08-08 | 2021-12-07 | Neuralmagic Inc. | System and method of accelerating execution of a neural network |
| US11194549B2 (en) * | 2019-10-25 | 2021-12-07 | Arm Limited | Matrix multiplication system, apparatus and method |
| US20210200711A1 (en) * | 2019-12-28 | 2021-07-01 | Intel Corporation | System and Method for Configurable Systolic Array with Partial Read/Write |
| US12566958B2 (en) | 2020-01-14 | 2026-03-03 | Red Hat, Inc. | System and method of training a neural network |
| US11614920B2 (en) * | 2020-05-07 | 2023-03-28 | Meta Platforms, Inc. | Bypassing zero-value multiplications in a hardware multiplier |
| US12530573B1 (en) | 2020-05-19 | 2026-01-20 | Red Hat, Inc. | Efficient execution of group-sparsified neural networks |
| KR102724444B1 (ko) * | 2020-07-10 | 2024-11-01 | 삼성전자주식회사 | 전자 장치 및 그의 제어 방법 |
| CN114065123A (zh) * | 2020-07-31 | 2022-02-18 | 华为技术有限公司 | 稀疏矩阵计算方法及加速装置 |
| TWI746126B (zh) * | 2020-08-25 | 2021-11-11 | 創鑫智慧股份有限公司 | 矩陣乘法裝置及其操作方法 |
| US11556757B1 (en) | 2020-12-10 | 2023-01-17 | Neuralmagic Ltd. | System and method of executing deep tensor columns in neural networks |
| CN112579519B (zh) * | 2021-03-01 | 2021-05-25 | 湖北芯擎科技有限公司 | 数据运算电路和处理芯片 |
| US12072952B2 (en) * | 2021-03-26 | 2024-08-27 | Advanced Micro Devices, Inc. | Data compressor for approximation of matrices for matrix multiply operations |
| US12197533B2 (en) | 2021-03-26 | 2025-01-14 | Advanced Micro Devices, Inc. | Approximation of matrices for matrix multiply operations |
| CN116888591A (zh) * | 2021-03-31 | 2023-10-13 | 华为技术有限公司 | 一种矩阵乘法器、矩阵计算方法及相关设备 |
| US12423379B2 (en) * | 2021-07-06 | 2025-09-23 | Google Llc | In situ sparse matrix expansion |
| US20230086275A1 (en) * | 2021-09-22 | 2023-03-23 | Intel Corporation | Emulation of floating point calculation |
| US20230102279A1 (en) * | 2021-09-25 | 2023-03-30 | Intel Corporation | Apparatuses, methods, and systems for instructions for structured-sparse tile matrix fma |
| US11960982B1 (en) | 2021-10-21 | 2024-04-16 | Neuralmagic, Inc. | System and method of determining and executing deep tensor columns in neural networks |
| US12399743B2 (en) | 2022-02-23 | 2025-08-26 | International Business Machines Corporation | Padding input data for artificial intelligence accelerators |
| KR20250002475A (ko) * | 2022-05-26 | 2025-01-07 | 구글 엘엘씨 | 행렬 연산을 위한 명령어 세트 아키텍처 |
| JP2023180060A (ja) * | 2022-06-08 | 2023-12-20 | 富士通株式会社 | 演算処理プログラムおよび演算処理方法 |
| CN114816434B (zh) * | 2022-06-28 | 2022-10-04 | 之江实验室 | 一种面向可编程交换的硬件解析器及解析器实现方法 |
| CN115310037B (zh) * | 2022-08-17 | 2026-02-17 | 杭州中天微系统有限公司 | 矩阵乘法计算装置、加速装置、计算系统和相关方法 |
| US12547546B2 (en) | 2022-10-13 | 2026-02-10 | International Business Machines Corporation | Processing tensors |
| CN120020761A (zh) * | 2023-11-17 | 2025-05-20 | 华为技术有限公司 | 稀疏矩阵的运算方法、处理器和计算设备 |
| KR20250160658A (ko) | 2024-05-07 | 2025-11-14 | 리벨리온 주식회사 | 데이터 연산 장치 및 방법 |
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| GB8320362D0 (en) * | 1983-07-28 | 1983-09-01 | Secr Defence | Digital data processor |
| US4603398A (en) * | 1984-02-17 | 1986-07-29 | The United States Of America As Represented By The Secretary Of The Navy | Matrix-matrix multiplication using an electrooptical systolic/engagement array processing architecture |
| GB8910960D0 (en) * | 1989-05-12 | 1989-06-28 | Secr Defence | Digital processor for two's complement computations |
| US8782115B1 (en) * | 2008-04-18 | 2014-07-15 | Altera Corporation | Hardware architecture and scheduling for high performance and low resource solution for QR decomposition |
| US8473540B1 (en) * | 2009-09-01 | 2013-06-25 | Xilinx, Inc. | Decoder and process therefor |
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| US9317482B2 (en) | 2012-10-14 | 2016-04-19 | Microsoft Technology Licensing, Llc | Universal FPGA/ASIC matrix-vector multiplication architecture |
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| US9697176B2 (en) * | 2014-11-14 | 2017-07-04 | Advanced Micro Devices, Inc. | Efficient sparse matrix-vector multiplication on parallel processors |
| US20160179470A1 (en) * | 2014-12-23 | 2016-06-23 | Shay Gueron | Method and apparatus for performing big-integer arithmetic operations |
| US10996959B2 (en) * | 2015-01-08 | 2021-05-04 | Technion Research And Development Foundation Ltd. | Hybrid processor |
| US10275247B2 (en) | 2015-03-28 | 2019-04-30 | Intel Corporation | Apparatuses and methods to accelerate vector multiplication of vector elements having matching indices |
| US9558156B1 (en) * | 2015-11-24 | 2017-01-31 | International Business Machines Corporation | Sparse matrix multiplication using a single field programmable gate array module |
| US10360163B2 (en) * | 2016-10-27 | 2019-07-23 | Google Llc | Exploiting input data sparsity in neural network compute units |
| US10346507B2 (en) * | 2016-11-01 | 2019-07-09 | Nvidia Corporation | Symmetric block sparse matrix-vector multiplication |
| US9959247B1 (en) * | 2017-02-17 | 2018-05-01 | Google Llc | Permuting in a matrix-vector processor |
| US10387122B1 (en) * | 2018-05-04 | 2019-08-20 | Olsen Ip Reserve, Llc | Residue number matrix multiplier |
-
2018
- 2018-06-08 US US16/003,545 patent/US10599429B2/en active Active
-
2019
- 2019-05-03 ES ES19172622T patent/ES2988859T3/es active Active
- 2019-05-03 PL PL19172622.3T patent/PL3579117T3/pl unknown
- 2019-05-03 EP EP20198971.2A patent/EP3772000A1/en not_active Ceased
- 2019-05-03 EP EP19172622.3A patent/EP3579117B1/en active Active
- 2019-05-22 CN CN202411126810.1A patent/CN119166216A/zh active Pending
- 2019-05-22 CN CN201910431218.5A patent/CN110580175A/zh active Pending
- 2019-05-22 CN CN202010944726.6A patent/CN112099852B/zh active Active
-
2020
- 2020-07-06 US US16/921,838 patent/US20200334038A1/en not_active Abandoned
Also Published As
| Publication number | Publication date |
|---|---|
| US10599429B2 (en) | 2020-03-24 |
| US20190042250A1 (en) | 2019-02-07 |
| CN110580175A (zh) | 2019-12-17 |
| EP3772000A1 (en) | 2021-02-03 |
| EP3579117B1 (en) | 2024-05-29 |
| CN112099852A (zh) | 2020-12-18 |
| EP3579117A1 (en) | 2019-12-11 |
| US20200334038A1 (en) | 2020-10-22 |
| ES2988859T3 (es) | 2024-11-21 |
| CN112099852B (zh) | 2024-08-30 |
| CN119166216A (zh) | 2024-12-20 |
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