JP7899185B2 - 階層的な共有指数浮動小数点データタイプ - Google Patents

階層的な共有指数浮動小数点データタイプ

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Publication number
JP7899185B2
JP7899185B2 JP2023541370A JP2023541370A JP7899185B2 JP 7899185 B2 JP7899185 B2 JP 7899185B2 JP 2023541370 A JP2023541370 A JP 2023541370A JP 2023541370 A JP2023541370 A JP 2023541370A JP 7899185 B2 JP7899185 B2 JP 7899185B2
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JP
Japan
Prior art keywords
value
shared
values
floating
point
Prior art date
Legal status (The legal status 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 status listed.)
Active
Application number
JP2023541370A
Other languages
English (en)
Japanese (ja)
Other versions
JP2024508596A5 (enExample
JP2024508596A (ja
Inventor
ロウハーニー，ビタ ダルビッシュ
エランゴ，ヴェンムギル
シャフィプール，ラスール
フォワーズ，ジェレミー
ガン リウ，ミン
シー，ジンウェン
シー． バーガー，ダグラス
エス． チュン，エリック
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Microsoft Technology Licensing LLC
Original Assignee
Microsoft Technology Licensing LLC
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Publication date
Application filed by Microsoft Technology Licensing LLC filed Critical Microsoft Technology Licensing LLC
Priority claimed from PCT/US2022/013086 external-priority patent/WO2022173572A1/en
Publication of JP2024508596A publication Critical patent/JP2024508596A/ja
Publication of JP2024508596A5 publication Critical patent/JP2024508596A5/ja
Application granted granted Critical
Publication of JP7899185B2 publication Critical patent/JP7899185B2/ja
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Classifications

    • 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
    • G06F7/483—Computations with numbers represented by a non-linear combination of denominational numbers, e.g. rational numbers, logarithmic number system or floating-point numbers
    • 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
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/14—Conversion to or from non-weighted codes
    • H03M7/24—Conversion to or from floating-point codes
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Nonlinear Science (AREA)
  • Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Computational Linguistics (AREA)
  • Neurology (AREA)
  • Artificial Intelligence (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Complex Calculations (AREA)
  • Electromagnetism (AREA)
JP2023541370A 2021-02-10 2022-01-20 階層的な共有指数浮動小数点データタイプ Active JP7899185B2 (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US202163148086P 2021-02-10 2021-02-10
US63/148,086 2021-02-10
US17/361,263 2021-06-28
US17/361,263 US11886833B2 (en) 2021-02-10 2021-06-28 Hierarchical and shared exponent floating point data types
PCT/US2022/013086 WO2022173572A1 (en) 2021-02-10 2022-01-20 Hierarchical and shared exponent floating point data types

Publications (3)

Publication Number Publication Date
JP2024508596A JP2024508596A (ja) 2024-02-28
JP2024508596A5 JP2024508596A5 (enExample) 2024-12-27
JP7899185B2 true JP7899185B2 (ja) 2026-08-03

Family

ID=82704967

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2023541370A Active JP7899185B2 (ja) 2021-02-10 2022-01-20 階層的な共有指数浮動小数点データタイプ

Country Status (6)

Country Link
US (1) US11886833B2 (enExample)
EP (1) EP4291979A1 (enExample)
JP (1) JP7899185B2 (enExample)
KR (1) KR20230137356A (enExample)
CN (1) CN116830077A (enExample)
TW (1) TWI913392B (enExample)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240402993A1 (en) * 2023-05-30 2024-12-05 Microsoft Technology Licensing, Llc Determining shared exponent values for shared exponent floating point data types

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190347072A1 (en) 2018-05-08 2019-11-14 Microsoft Technology Licensing, Llc Block floating point computations using shared exponents
JP2019212295A (ja) 2018-06-08 2019-12-12 インテル・コーポレーション フレキシブルな浮動小数点テンソルを用いた人工ニューラルネットワーク訓練
JP2021536076A (ja) 2018-09-19 2021-12-23 ザイリンクス インコーポレイテッドXilinx Incorporated 乗算累積回路

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8301803B2 (en) 2009-10-23 2012-10-30 Samplify Systems, Inc. Block floating point compression of signal data
WO2013003479A2 (en) 2011-06-30 2013-01-03 Samplify Systems, Inc. Compression of floating-point data
US9891887B2 (en) 2014-07-02 2018-02-13 Via Alliance Semiconductor Co., Ltd Subdivision of a fused compound arithmetic operation
US12141689B2 (en) 2019-03-18 2024-11-12 Nvidia Corporation Data compression for a neural network
US11934797B2 (en) 2019-04-04 2024-03-19 Intel Corporation Mechanism to perform single precision floating point extended math operations

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190347072A1 (en) 2018-05-08 2019-11-14 Microsoft Technology Licensing, Llc Block floating point computations using shared exponents
JP2019212295A (ja) 2018-06-08 2019-12-12 インテル・コーポレーション フレキシブルな浮動小数点テンソルを用いた人工ニューラルネットワーク訓練
JP2021536076A (ja) 2018-09-19 2021-12-23 ザイリンクス インコーポレイテッドXilinx Incorporated 乗算累積回路

Also Published As

Publication number Publication date
US20220253281A1 (en) 2022-08-11
EP4291979A1 (en) 2023-12-20
TWI913392B (zh) 2026-02-01
US11886833B2 (en) 2024-01-30
TW202234229A (zh) 2022-09-01
CN116830077A (zh) 2023-09-29
JP2024508596A (ja) 2024-02-28
KR20230137356A (ko) 2023-10-04

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