FI20215475A1 - Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning - Google Patents
Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning Download PDFInfo
- Publication number
- FI20215475A1 FI20215475A1 FI20215475A FI20215475A FI20215475A1 FI 20215475 A1 FI20215475 A1 FI 20215475A1 FI 20215475 A FI20215475 A FI 20215475A FI 20215475 A FI20215475 A FI 20215475A FI 20215475 A1 FI20215475 A1 FI 20215475A1
- Authority
- FI
- Finland
- Prior art keywords
- matrix
- voltage
- matrix accelerator
- processing system
- accelerator
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims description 46
- 238000004422 calculation algorithm Methods 0.000 title description 12
- 239000011159 matrix material Substances 0.000 claims description 140
- 238000012545 processing Methods 0.000 claims description 58
- 238000001514 detection method Methods 0.000 claims description 46
- 230000008569 process Effects 0.000 claims description 12
- 238000003491 array Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 8
- 230000003190 augmentative effect Effects 0.000 claims description 5
- 206010052804 Drug tolerance Diseases 0.000 claims description 2
- 241000288147 Meleagris gallopavo Species 0.000 claims description 2
- QHGVXILFMXYDRS-UHFFFAOYSA-N pyraclofos Chemical compound C1=C(OP(=O)(OCC)SCCC)C=NN1C1=CC=C(Cl)C=C1 QHGVXILFMXYDRS-UHFFFAOYSA-N 0.000 claims description 2
- 230000001276 controlling effect Effects 0.000 claims 7
- PPTYJKAXVCCBDU-UHFFFAOYSA-N Rohypnol Chemical compound N=1CC(=O)N(C)C2=CC=C([N+]([O-])=O)C=C2C=1C1=CC=CC=C1F PPTYJKAXVCCBDU-UHFFFAOYSA-N 0.000 abstract 1
- 238000013461 design Methods 0.000 description 17
- 238000013459 approach Methods 0.000 description 12
- 238000004088 simulation Methods 0.000 description 12
- 238000012937 correction Methods 0.000 description 7
- 230000008901 benefit Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000009467 reduction Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 230000006854 communication Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 239000013598 vector Substances 0.000 description 4
- 238000013528 artificial neural network Methods 0.000 description 3
- 230000006399 behavior Effects 0.000 description 3
- 230000002787 reinforcement Effects 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000008713 feedback mechanism Effects 0.000 description 2
- 241001527806 Iti Species 0.000 description 1
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 229910052729 chemical element Inorganic materials 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000000280 densification Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000019634 flavors Nutrition 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 230000002459 sustained effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 230000008685 targeting Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 230000017105 transposition Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/0766—Error or fault reporting or storing
- G06F11/0772—Means for error signaling, e.g. using interrupts, exception flags, dedicated error registers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
- G06F1/3296—Power saving characterised by the action undertaken by lowering the supply or operating voltage
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/28—Supervision thereof, e.g. detecting power-supply failure by out of limits supervision
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
- G06F1/3234—Power saving characterised by the action undertaken
- G06F1/324—Power saving characterised by the action undertaken by lowering clock frequency
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/004—Error avoidance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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; CALCULATING OR 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
- H03K—PULSE TECHNIQUE
- H03K19/00—Logic circuits, i.e. having at least two inputs acting on one output; Inverting circuits
- H03K19/0008—Arrangements for reducing power consumption
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03K—PULSE TECHNIQUE
- H03K19/00—Logic circuits, i.e. having at least two inputs acting on one output; Inverting circuits
- H03K19/003—Modifications for increasing the reliability for protection
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03K—PULSE TECHNIQUE
- H03K3/00—Circuits for generating electric pulses; Monostable, bistable or multistable circuits
- H03K3/02—Generators characterised by the type of circuit or by the means used for producing pulses
- H03K3/027—Generators characterised by the type of circuit or by the means used for producing pulses by the use of logic circuits, with internal or external positive feedback
- H03K3/037—Bistable circuits
- H03K3/0375—Bistable circuits provided with means for increasing reliability; for protection; for ensuring a predetermined initial state when the supply voltage has been applied; for storing the actual state when the supply voltage fails
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Computing Systems (AREA)
- Data Mining & Analysis (AREA)
- Quality & Reliability (AREA)
- Biomedical Technology (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Biophysics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Neurology (AREA)
- Artificial Intelligence (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Medicines Containing Plant Substances (AREA)
- Power Sources (AREA)
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FI20215475A FI130137B (sv) | 2021-04-22 | 2021-04-22 | Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning |
PCT/FI2022/050258 WO2022223881A1 (en) | 2021-04-22 | 2022-04-20 | A method for increase of energy efficiency through leveraging fault tolerant algorithms into undervolted digital systems |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FI20215475A FI130137B (sv) | 2021-04-22 | 2021-04-22 | Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning |
Publications (2)
Publication Number | Publication Date |
---|---|
FI20215475A1 true FI20215475A1 (sv) | 2022-10-23 |
FI130137B FI130137B (sv) | 2023-03-09 |
Family
ID=81850667
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
FI20215475A FI130137B (sv) | 2021-04-22 | 2021-04-22 | Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning |
Country Status (2)
Country | Link |
---|---|
FI (1) | FI130137B (sv) |
WO (1) | WO2022223881A1 (sv) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11710030B2 (en) * | 2018-08-31 | 2023-07-25 | Texas Instmments Incorporated | Fault detectable and tolerant neural network |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE1774906A1 (de) | 1967-10-30 | 1971-11-04 | Olivetti & Co Spa | Dezimalrechenmaschine |
US7278080B2 (en) | 2003-03-20 | 2007-10-02 | Arm Limited | Error detection and recovery within processing stages of an integrated circuit |
CN101369241A (zh) | 2007-09-21 | 2009-02-18 | 中国科学院计算技术研究所 | 一种机群容错系统、装置及方法 |
US20120221884A1 (en) | 2011-02-28 | 2012-08-30 | Carter Nicholas P | Error management across hardware and software layers |
US10908668B2 (en) * | 2017-12-29 | 2021-02-02 | Intel Corporation | Voltage droop mitigation technology in array processor cores |
CN108733628B (zh) | 2018-05-23 | 2020-01-03 | 河海大学常州校区 | 一种并行矩阵乘算法的加固方法 |
CN110932713B (zh) * | 2019-11-11 | 2023-05-16 | 东南大学 | 用于卷积神经网络硬件加速器的时序弹性电路 |
-
2021
- 2021-04-22 FI FI20215475A patent/FI130137B/sv active
-
2022
- 2022-04-20 WO PCT/FI2022/050258 patent/WO2022223881A1/en active Application Filing
Also Published As
Publication number | Publication date |
---|---|
FI130137B (sv) | 2023-03-09 |
WO2022223881A1 (en) | 2022-10-27 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Mittal | A survey on modeling and improving reliability of DNN algorithms and accelerators | |
Venkataramani et al. | Substitute-and-simplify: A unified design paradigm for approximate and quality configurable circuits | |
Wu et al. | An efficient method for calculating the error statistics of block-based approximate adders | |
EP3035254A1 (en) | Method of managing the operation of an electronic system with a guaranteed lifetime | |
Safarpour et al. | Algorithm level error detection in low voltage systolic array | |
Wang et al. | Resilience-aware frequency tuning for neural-network-based approximate computing chips | |
Damsgaard et al. | Approximation opportunities in edge computing hardware: A systematic literature review | |
Chen et al. | Two approximate voting schemes for reliable computing | |
FI130137B (sv) | Förfarande för ökning av energieffektivitet genom att utnyttja feltoleranta algoritmer för digitala system med underspänning | |
Taheri et al. | Deepaxe: A framework for exploration of approximation and reliability trade-offs in dnn accelerators | |
Salamin et al. | Reliability-aware quantization for anti-aging NPUs | |
Jiao et al. | Tevot: Timing error modeling of functional units under dynamic voltage and temperature variations | |
Ozen et al. | Architecting decentralization and customizability in dnn accelerators for hardware defect adaptation | |
Huang et al. | Sensor-based approximate adder design for accelerating error-tolerant and deep-learning applications | |
Chen et al. | Design and evaluation of confidence-driven error-resilient systems | |
Kong et al. | M2STaR: A Multi-Mode Spatio-Temporal Redundancy Design for Fault-Tolerant Coarse-Grained Reconfigurable Architectures | |
Huang et al. | A determinate radiation hardened technique for safety-critical CMOS designs | |
Deepanjali et al. | Self healing controllers to mitigate SEU in the control path of FPGA based system: A complete intrinsic evolutionary approach | |
Liu et al. | Runtime long-term reliability management using stochastic computing in deep neural networks | |
Marty et al. | Algorithm level timing speculation for convolutional neural network accelerators | |
Tsounis et al. | A methodology for fault-tolerant pareto-optimal approximate designs of fpga-based accelerators | |
Santiago et al. | Characterizing approximate adders and multipliers for mitigating aging and temperature degradations | |
Ikezoe et al. | Recovering faulty non-volatile flip flops for coarse-grained reconfigurable architectures | |
Abdallah et al. | Timing error statistics for energy-efficient robust DSP systems | |
Juliato et al. | SEU-resistant SHA-256 design for security in satellites |