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Title: GitHub - MPSLab-ASU/ML-Accelerators: Topics in Machine Learning Accelerator Design

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Description: Topics in Machine Learning Accelerator Design. Contribute to MPSLab-ASU/ML-Accelerators development by creating an account on GitHub.

Open Graph Description: Topics in Machine Learning Accelerator Design. Contribute to MPSLab-ASU/ML-Accelerators development by creating an account on GitHub.

X Description: Topics in Machine Learning Accelerator Design. Contribute to MPSLab-ASU/ML-Accelerators development by creating an account on GitHub.

Opengraph URL: https://github.com/MPSLab-ASU/ML-Accelerators

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LICENSE	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators/blob/main/LICENSE
LICENSE	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators/blob/main/LICENSE
README.md	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators/blob/main/README.md
README.md	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators/blob/main/README.md
README	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators
Apache-2.0 license	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#topics-in-machine-learning-accelerator-design
"Topics in Machine Learning Design" (CEN/CSE 598)	https://labs.engineering.asu.edu/mps-lab/teaching/mla/
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#table-of-contents
Reference Books	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#books
Reference Surveys	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#surveys
Overview of Machine Learning and Deep Learning Models	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#ml-models
DNN Model Inference and Training	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#training-inference
Various Deep Learning Models	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#various-models
Additional Readings	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#ml-models-additional-readings
Introduction to DNN accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#intro-dnn-accelerators
CNN/GEMM Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#cnn-gemm-accelerators
NoCs for ML Accelerator	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#nocs-accelerators
Memory Design for ML Accelerator	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#accelerator-memory
Accelerators for NLP	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#nlp-accelerators
Accelerating RNNs and LSTMs	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#rnn-lstm
Accelerating Transformers	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#transformers
Neuromorphic Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#neuromorphic
Accelerator Design Frameworks and Hardware/Software Codesign Optimizations	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#hw-sw-codesign
Accelerator Execution Cost Modeling	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#execution-cost
Design Libraries and Frameworks	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#design-frameworks
DNN-to-Accelerator Mapping Optimizations	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#mapping-optimizations
Programming Languages and Compilers for Accelerator Generation	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#design-by-pl-compilers
Accelerator Hardware/Software Design Space Exploration	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#dse
Compilers for ML Accelerators and Machine Code Generation	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#compilers-codegen
Compilers for ML Accelerator	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#compilers
Domain-Specific Languages (DSLs) for ML Accelerator Programming	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#dsls
Intermediate Representations (IRs)	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#irs
Automated Cost Generation with Machine/Deep Learning	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#automated-costs
ISAs and Machine Code Generation	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#codegen
Accelerators for ML Training	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#training-accelerators
Architectural Support for Quantization	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#quantization
Model Compression Techniques	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#model-compression
Quantization Techniques	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#quantization-methods
Bit-Adaptive Computing	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#bit-adaptive-computing
Leveraging Value Similarity	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#value-similarity
Aggressive Quantization (Binary, Ternary, Logarithmic)	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#binary-logarithmic
Sparse ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#sparse-mla
Accelerator-aware Neural-architecture Search and Accelerator/Model Codesigns	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#nas-and-model-mla-codesign
Neural Architecture Search Techniques	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#nas-techniques
Hardware-aware Neural Architecture Search	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#hw-aware-nas
Accelerator-aware Neural Architecture Search	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#accelerator-aware-nas
Accelerator Design for Multiple workloads and Multi-chip Accelerator Designs	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#multiple-workloads-multiple-mlas
Resource Partitioning of Workloads on One or More Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#resource-partitioning
Accelerator for Multiple Workloads	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#multi-workloads
NoCs for Chiplets	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#noc-chiplets
Scalability Analysis	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#mlas-scalability-analysis
ML Accelerators with Near-Data Processing and In-Memory Computing	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#neardata-pim
ML Accelerators with Near-Data Processing	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#neardata
In-Memory Acceleration	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#pim
Emerging Technologies	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#emerging-tech
Photonics Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#photonics
Stochastic Computing Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#stochastic-computing
Accelerators for Recommendation Systems	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#recommendation
Accelerators for Graph Learning	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#graph-learning
Accelerators for Other AI Domains	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#other-domains
Accelerator Benchmarking and Workload Characterizations	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#benchmarks-characterizations
ML Benchmarks for Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#benchmarks
Accelerator/Workload Characterizations for Various Deployment Scenarios	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#characterizations
Simulators for ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#simulators
Runtime Optimizations	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#runtime
Distributed Inference and Collaborative Cloud/Edge Execution	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#cloud-edge-collaborative
Dynamic Adaptations	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#dynamic-adaptation
On-device and Federated Learning on ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#federated-ondevice-learning
On-device Learning	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#ondevice-learning
Federated Learning	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#federated-learning
Industry Case Studies (Established Startups)	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#industry-startups
Recent Industrial ML Hardware Avenues	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#industry-hardware-startups
Recent Industrial ML Software Avenues	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#industry-software-startups
Industry Case Studies	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#industry
Reliability and Security of ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#reliability-security
Reliability of ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#reliability
Security of ML Accelerators	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#security
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-reference-books
Book	https://www.morganclaypool.com/doi/abs/10.2200/S01004ED1V01Y202004CAC050
Book	https://www.morganclaypool.com/doi/10.2200/S01046ED1V01Y202009CAC053
https://deeplearningsystems.ai/	https://deeplearningsystems.ai/
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-reference-surveys
Paper	https://www.rle.mit.edu/eems/wp-content/uploads/2017/11/2017_pieee_dnn.pdf
Paper	https://ieeexplore.ieee.org/abstract/document/9043731
Paper	https://ieeexplore.ieee.org/abstract/document/9507542/
Paper	https://arxiv.org/abs/2002.03794
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-overview-of-machine-learning-and-deep-learning-models
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-dnn-model-inference-and-training
Online Book	http://neuralnetworksanddeeplearning.com/
Videos	https://www.youtube.com/watch?v=Ijqkc7OLenI
Chapter1	http://neuralnetworksanddeeplearning.com/chap1.html
Chapter2	http://neuralnetworksanddeeplearning.com/chap2.html
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-various-deep-learning-models
Chapter3	https://deeplearningsystems.ai/#ch03/
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-additional-readings
Paper	https://www.rle.mit.edu/eems/wp-content/uploads/2017/11/2017_pieee_dnn.pdf
Paper	https://www.mdpi.com/2079-9292/8/3/292/htm
Paper	https://courses.cs.duke.edu/spring20/compsci527/papers/Pouyanfar.pdf
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#--introduction-to-dnn-accelerators
Paper	https://www.rle.mit.edu/eems/wp-content/uploads/2016/11/eyeriss_jssc_2017.pdf
Paper	https://www.cs.virginia.edu/~smk9u/CS6501F16/p609-chen.pdf
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-cnngemm-accelerators
Paper	https://arxiv.org/abs/1704.04760
Paper	https://www.intel.com/content/dam/www/programmable/us/en/pdfs/literature/wp/wp-microsoft-serving-dnns-in-real-time.pdf
Paper	https://cpn-us-w2.wpmucdn.com/sites.gatech.edu/dist/c/332/files/2018/01/maeri_asplos2018.pdf
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-nocs-for-ml-accelerator
Paper	https://arxiv.org/pdf/2007.00864.pdf
Paper	https://arxiv.org/abs/2103.10515
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-memory-design-for-ml-accelerator
Paper	https://people.eecs.berkeley.edu/~ysshao/assets/papers/Buffet_ASPLOS19_Final.pdf
Paper	https://polyarch.cs.ucla.edu/papers/micro2019-spu.pdf
Paper	https://web.engr.oregonstate.edu/~chenliz/publications/2019_HPCA_Shortcut%20Mining.pdf
Paper	http://www.ece.sunysb.edu/~pmilder/papers/16micro.pdf
Paper	https://arxiv.org/pdf/2007.00864.pdf
	https://patch-diff.githubusercontent.com/MPSLab-ASU/ML-Accelerators#-accelerators-for-nlp
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Paper	https://ieeexplore.ieee.org/abstract/document/9387491
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Paper	https://dl.acm.org/doi/abs/10.1145/3372780.3380846
Paper	https://arxiv.org/pdf/2112.13896.pdf
Paper	https://ieeexplore.ieee.org/abstract/document/9018203
Slides	https://ieeexplore.ieee.org/abstract/document/8875671
Paper	https://www.graphcore.ai/hubfs/assets/pdf/Citadel%20Securities%20Technical%20Report%20-%20Dissecting%20the%20Graphcore%20IPU%20Architecture%20via%20Microbenchmarking%20Dec%202019.pdf
Paper	https://groq.com/wp-content/uploads/2020/06/ISCA-TSP.pdf
Webpage	https://www.mythic-ai.com/technology/
Blog	https://www.mythic-ai.com/the-future-of-ai-twenty-trillion-synapses/
Talks	https://www.youtube.com/watch?v=pGXWNoO5Q3M
Paper	https://research.cs.wisc.edu/vertical/papers/2022/isca22-mozart.pdf
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Blog	https://neuralmagic.com/technology/
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GitHub	https://github.com/mosaicml/composer
Docs	https://docs.mosaicml.com/en/v0.5.0/
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Paper	https://arxiv.org/pdf/2107.04140
Paper	https://ieeexplore.ieee.org/abstract/document/9499913
Blog	https://developer.nvidia.com/blog/nvidia-ampere-architecture-in-depth/
Blog	https://developer.nvidia.com/blog/nvidia-hopper-architecture-in-depth/
Paper	https://ieeexplore.ieee.org/abstract/document/9499876
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Paper	https://people.csail.mit.edu/emer/papers/2017.11.sc.error_propagation_in_DNNs.pdf
Paper	https://dl.acm.org/doi/10.1145/3195970.3195997
Paper	https://www.sciencedirect.com/science/article/pii/S1383762119304965?casa_token=zs060XSD2NcAAAAA:HNav3CwZQCY7ip0YFRvd73KVvgPfS9huyUY58HnU2Degmc-ro0rrXLrhYky2dfuNs4Djqxi-
Paper	https://www.researchgate.net/profile/Lars-Bauer-2/publication/261164817_Reliable_On-chip_systems_in_the_nano-era_Lessons_learnt_and_future_trends/links/53cedb3c0cf2f7e53cf7e27f/Reliable-On-chip-systems-in-the-nano-era-Lessons-learnt-and-future-trends.pdf
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Paper	https://dl.acm.org/doi/abs/10.1145/3195970.3196023
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Paper	https://arxiv.org/pdf/1710.00942.pdf
Paper	https://openaccess.thecvf.com/content_ICCV_2019/papers/Rakin_Bit-Flip_Attack_Crushing_Neural_Network_With_Progressive_Bit_Search_ICCV_2019_paper.pdf
Paper	https://arxiv.org/pdf/1712.05526.pdf
Paper	https://people.cs.uchicago.edu/~ravenben/publications/pdf/backdoor-sp19.pdf
Paper	https://arxiv.org/pdf/1805.12185
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Prof. Aviral Shrivastava	https://labs.engineering.asu.edu/mps-lab/person/aviral-shrivastava/
Shail Dave	https://sites.google.com/view/shail
Make Programming Simple Lab	https://labs.engineering.asu.edu/mps-lab/updates
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