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Oral
Mon Mar 02 06:00 AM -- 06:25 AM (PST) @ Ballroom A
A System for Massively Parallel Hyperparameter Tuning
In Distributed and Parallel Learning Algorithms
Liam Li · Kevin Jamieson · Afshin Rostamizadeh · Ekaterina Gonina · Jonathan Ben-tzur · Moritz Hardt · Benjamin Recht · Ameet Talwalkar
Oral
Mon Mar 02 06:25 AM -- 06:50 AM (PST) @ Ballroom A #102
PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud
In Distributed and Parallel Learning Algorithms
Liang Luo · Peter West · Jacob Nelson · Arvind Krishnamurthy · Luis Ceze
Oral
Mon Mar 02 06:50 AM -- 07:15 AM (PST) @ Ballroom A
Federated Optimization in Heterogeneous Networks
In Distributed and Parallel Learning Algorithms
Tian Li · Anit Kumar Sahu · Manzil Zaheer · Maziar Sanjabi · Ameet Talwalkar · Virginia Smith
Break
Mon Mar 02 07:00 AM -- 07:45 AM (PST) @ Ballroom B
Breakfast and Registration
Oral
Mon Mar 02 07:15 AM -- 07:40 AM (PST) @ Ballroom A
BPPSA: Scaling Back-propagation by Parallel Scan Algorithm
In Distributed and Parallel Learning Algorithms
Shang Wang · Yifan Bai · Gennady Pekhimenko
Oral
Mon Mar 02 07:40 AM -- 08:05 AM (PST) @ Ballroom A
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
In Distributed and Parallel Learning Algorithms
Weijie Zhao · Deping Xie · Ronglai Jia · Yulei Qian · Ruiquan Ding · Mingming Sun · Ping Li
Break
Mon Mar 02 07:45 AM -- 08:00 AM (PST) @ Ballroom A
Opening Remarks
Oral
Mon Mar 02 08:30 AM -- 08:55 AM (PST) @ Ballroom A
Resource Elasticity in Distributed Deep Learning
In Efficient Model Training
Andrew Or · Haoyu Zhang · Michael None Freedman
Oral
Mon Mar 02 08:55 AM -- 09:20 AM (PST) @ Ballroom A
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
In Efficient Model Training
Beidi Chen · Tharun Medini · James Farwell · sameh gobriel · Charlie Tai · Anshumali Shrivastava
Oral
Mon Mar 02 09:20 AM -- 09:45 AM (PST) @ Ballroom A
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks
In Efficient Model Training
Hui Guan · Laxmikant Kishor Mokadam · Xipeng Shen · Seung-Hwan Lim · Robert Patton
Oral
Mon Mar 02 09:45 AM -- 10:10 AM (PST) @ Ballroom A
Breaking the Memory Wall with Optimal Tensor Rematerialization
In Efficient Model Training
Paras Jain · Ajay Jain · Aniruddha Nrusimha · Amir Gholami · Pieter Abbeel · Joseph Gonzalez · Kurt Keutzer · Ion Stoica
Break
Mon Mar 02 10:05 AM -- 10:30 AM (PST)
Coffee Break
Invited Talk
Mon Mar 02 11:30 AM -- 12:30 PM (PST) @ Ballroom A
Theory and Systems for Weak Supervision
Christopher Ré
[ Video] 
Break
Mon Mar 02 12:10 PM -- 01:30 PM (PST) @ Ballroom B + C
Lunch will be provided
Oral
Mon Mar 02 12:30 PM -- 12:55 PM (PST) @ Ballroom A
What is the State of Neural Network Pruning?
In Efficient Inference and Model Serving
Davis Blalock · Jose Javier Gonzalez Ortiz · Jonathan Frankle · John Guttag
Oral
Mon Mar 02 12:55 PM -- 01:20 PM (PST) @ Ballroom A
SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems
In Efficient Inference and Model Serving
Xiaofan Zhang · Haoming Lu · Cong Hao · Jiachen Li · Bowen Cheng · Yuhong Li · Kyle Rupnow · Jinjun Xiong · Thomas Huang · Honghui Shi · Wen-Mei Hwu · Deming Chen
Oral
Mon Mar 02 01:20 PM -- 01:45 PM (PST) @ Ballroom A
MNN: A Universal and Efficient Inference Engine
In Efficient Inference and Model Serving
Xiaotang Jiang · Huan Wang · Yiliu Chen · Ziqi Wu · Lichuan Wang · Bin Zou · Yafeng Yang · Zongyang Cui · Yu Cai · Tianhang Yu · Chengfei Lyu · Zhihua Wu
Oral
Mon Mar 02 01:45 PM -- 02:10 PM (PST) @ Ballroom A
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference
In Efficient Inference and Model Serving
Peter Kraft · Daniel Kang · Deepak Narayanan · Shoumik Palkar · Peter Bailis · Matei Zaharia
Oral
Mon Mar 02 02:30 PM -- 02:55 PM (PST) @ Ballroom A
Attention-based Learning for Missing Data Imputation in HoloClean
In Model / Data Quality and Privacy
Richard Wu · Aoqian Zhang · Ihab Ilyas · Theodoros Rekatsinas
Oral
Mon Mar 02 02:55 PM -- 03:20 PM (PST) @ Ballroom A
Privacy-Preserving Bandits
In Model / Data Quality and Privacy
Mohammad Malekzadeh · Dimitrios Athanasakis · Hamed Haddadi · Ben Livshits
Oral
Mon Mar 02 03:20 PM -- 03:45 PM (PST) @ Ballroom A
Understanding the Downstream Instability of Word Embeddings
In Model / Data Quality and Privacy
Megan Leszczynski · Avner May · Jian Zhang · Sen Wu · Christopher Aberger · Christopher Re
Oral
Mon Mar 02 03:45 PM -- 04:10 PM (PST) @ Ballroom A
Model Assertions for Monitoring and Improving ML Models
In Model / Data Quality and Privacy
Daniel Kang · Deepti Raghavan · Peter Bailis · Matei Zaharia
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #101
Demonstration of Ballet: A Framework for Open-Source Collaborative Feature Engineering
In Demonstrations
Micah J Smith · Kelvin Lu · Kalyan Veeramachaneni
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #102
PlaidML EDSL: Combining Programmability and Portability
In Demonstrations
Frank Laub · Denise Kutnick · Namrata Choudhury
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #106
3D Adversarial Object against MSF-based Perception in Autonomous Driving
In Demonstrations
Yulong Cao · Ningfei Wang · Chaowei Xiao · Dawei Yang · Jin Fang · Ruigang Yang · Qi Alfred Chen · Mingyan Liu · Bo Li
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #105
Visual Face Re Identification on a Battery-Powered Multi-Core Edge Processor
In Demonstrations
Manuele Rusci · Francesco Paci · Martin Croome · Maxim Zemlyanikin · Alexander Smorkalov (Russia Xperience AI) Smorkalov · Anna Petrovicheva
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #104
Air Learning: An End To End Learning Gym For Aerial Robots
In Demonstrations
Srivatsan Krishnan · Colby Banbury · Bardienus Duisterhof · Aleksandra Faust · Vijay Janapa Reddi
[ Slides] 
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #103
Skyline: Interactive In-editor Performance Visualizations and Debugging for DNN Training
In Demonstrations
Geoffrey Yu · Tovi Grossman · Gennady Pekhimenko
Demonstration
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C #100
Fairness Indicators Demo: Scalable Infrastructure for Fair ML Systems
In Demonstrations
Manasi Joshi · Christina Greer · Tulsee Doshi · Catherina Xu
Session
Mon Mar 02 04:00 PM -- 07:00 PM (PST) @ Ballroom B + C
Demonstrations
Break
Mon Mar 02 04:10 PM -- 04:30 PM (PST)
Coffee Break
Demonstration
Mon Mar 02 04:10 PM -- 04:15 PM (PST) @ Ballroom A
Demonstration Previews
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #1
A System for Massively Parallel Hyperparameter Tuning
In Posters and Reception
Liam Li · Kevin Jamieson · Afshin Rostamizadeh · Ekaterina Gonina · Jonathan Ben-tzur · Moritz Hardt · Benjamin Recht · Ameet Talwalkar
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #2
PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud
In Posters and Reception
Liang Luo · Peter West · Jacob Nelson · Arvind Krishnamurthy · Luis Ceze
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #3
Federated Optimization in Heterogeneous Networks
In Posters and Reception
Tian Li · Anit Kumar Sahu · Manzil Zaheer · Maziar Sanjabi · Ameet Talwalkar · Virginia Smith
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #4
BPPSA: Scaling Back-propagation by Parallel Scan Algorithm
In Posters and Reception
Shang Wang · Yifan Bai · Gennady Pekhimenko
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #5
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
In Posters and Reception
Weijie Zhao · Deping Xie · Ronglai Jia · Yulei Qian · Ruiquan Ding · Mingming Sun · Ping Li
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #6
Resource Elasticity in Distributed Deep Learning
In Posters and Reception
Andrew Or · Haoyu Zhang · Michael None Freedman
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #7
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
In Posters and Reception
Beidi Chen · Tharun Medini · James Farwell · sameh gobriel · Charlie Tai · Anshumali Shrivastava
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #8
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks
In Posters and Reception
Hui Guan · Laxmikant Kishor Mokadam · Xipeng Shen · Seung-Hwan Lim · Robert Patton
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #9
Breaking the Memory Wall with Optimal Tensor Rematerialization
In Posters and Reception
Paras Jain · Ajay Jain · Aniruddha Nrusimha · Amir Gholami · Pieter Abbeel · Joseph Gonzalez · Kurt Keutzer · Ion Stoica
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #10
What is the State of Neural Network Pruning?
In Posters and Reception
Davis Blalock · Jose Javier Gonzalez Ortiz · Jonathan Frankle · John Guttag
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #11
SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems
In Posters and Reception
Xiaofan Zhang · Haoming Lu · Cong Hao · Jiachen Li · Bowen Cheng · Yuhong Li · Kyle Rupnow · Jinjun Xiong · Thomas Huang · Honghui Shi · Wen-Mei Hwu · Deming Chen
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #12
MNN: A Universal and Efficient Inference Engine
In Posters and Reception
Xiaotang Jiang · Huan Wang · Yiliu Chen · Ziqi Wu · Lichuan Wang · Bin Zou · Yafeng Yang · Zongyang Cui · Yu Cai · Tianhang Yu · Chengfei Lyu · Zhihua Wu
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #13
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference
In Posters and Reception
Peter Kraft · Daniel Kang · Deepak Narayanan · Shoumik Palkar · Peter Bailis · Matei Zaharia
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #14
Attention-based Learning for Missing Data Imputation in HoloClean
In Posters and Reception
Richard Wu · Aoqian Zhang · Ihab Ilyas · Theodoros Rekatsinas
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #15
Privacy-Preserving Bandits
In Posters and Reception
Mohammad Malekzadeh · Dimitrios Athanasakis · Hamed Haddadi · Ben Livshits
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #16
Understanding the Downstream Instability of Word Embeddings
In Posters and Reception
Megan Leszczynski · Avner May · Jian Zhang · Sen Wu · Christopher Aberger · Christopher Re
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #17
Model Assertions for Monitoring and Improving ML Models
In Posters and Reception
Daniel Kang · Deepti Raghavan · Peter Bailis · Matei Zaharia
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #18
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning
In Posters and Reception
Ameer Haj-Ali · Qijing (Jenny) Huang · John Xiang · William Moses · Krste Asanovic · John Wawrzynek · Ion Stoica
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #19
Automatically batching control-intensive programs for modern accelerators
In Posters and Reception
Alexey Radul · Brian Patton · Dougal Maclaurin · Matthew Hoffman · Rif A. Saurous
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #20
Predictive Precompute with Recurrent Neural Networks
In Posters and Reception
Hanson Wang · Zehui Wang · Yuanyuan Ma
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #21
Sense & Sensitivities: The Path to General-Purpose Algorithmic Differentiation
In Posters and Reception
Mike Innes
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #22
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
In Posters and Reception
Byung Hoon Ahn · Jinwon Lee · Jamie Menjay Lin · Hsin-Pai Cheng · Jilei Hou · Hadi Esmaeilzadeh
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #23
Fine-Grained GPU Sharing Primitives for Deep Learning Applications
In Posters and Reception
Peifeng Yu · Mosharaf Chowdhury
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #24
Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc
In Posters and Reception
Zhihao Jia · Sina Lin · Mingyu Gao · Matei Zaharia · Alex Aiken
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #25
OPTIMUS: OPTImized matrix MUltiplication Structure for Transformer neural network accelerator
In Posters and Reception
Junki Park · Hyunsung Yoon · Daehyun Ahn · Jungwook Choi · Jae-Joon Kim
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #26
PoET-BiN: Power Efficient Tiny Binary Neurons
In Posters and Reception
Sivakumar Chidambaram · Pierre Langlois · Jean-Pierre David
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #27
Memory-Driven Mixed Low Precision Quantization for Enabling Deep Network Inference on Microcontrollers
In Posters and Reception
Manuele Rusci · Alessandro Capotondi · Luca Benini
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #28
Trained Quantization Thresholds for Accurate and Efficient Fixed-Point Inference of Deep Neural Networks
In Posters and Reception
Sambhav Jain · Albert Gural · Michael Wu · Chris Dick
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #29
Riptide: Fast End-to-End Binarized Neural Networks
In Posters and Reception
Joshua Fromm · Meghan Cowan · Matthai Philipose · Luis Ceze · Shwetak Patel
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #30
Searching for Winograd-aware Quantized Networks
In Posters and Reception
Javier Fernandez-Marques · Paul Whatmough · Andrew Mundy · Matthew Mattina
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #31
Blink: Fast and Generic Collectives for Distributed ML
In Posters and Reception
Guanhua Wang · Shivaram Venkataraman · Amar Phanishayee · Nikhil Devanur · Jorgen Thelin · Ion Stoica
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #32
A Systematic Methodology for Analysis of Deep Learning Hardware and Software Platforms
In Posters and Reception
Yu Wang · Gu-Yeon Wei · David Brooks
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #33
MotherNets: Rapid Deep Ensemble Learning
In Posters and Reception
Abdul Wasay · Brian Hentschel · Yuze Liao · Sanyuan Chen · Stratos Idreos
Poster
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A #34
MLPerf Training Benchmark
In Posters and Reception
Peter Mattson · Christine Cheng · Gregory Diamos · Cody Coleman · Paulius Micikevicius · David Patterson · Hanlin Tang · Gu-Yeon Wei · Peter Bailis · Victor Bittorf · David Brooks · Dehao Chen · Debo Dutta · Udit Gupta · Kim Hazelwood · Andy Hock · Xinyuan Huang · Daniel Kang · David Kanter · Naveen Kumar · Jeffery Liao · Deepak Narayanan · Tayo Oguntebi · Gennady Pekhimenko · Lillian Pentecost · Vijay Janapa Reddi · Taylor Robie · Tom St John · Carole-Jean Wu · Lingjie Xu · Cliff Young · Matei Zaharia
Session
Mon Mar 02 04:30 PM -- 07:00 PM (PST) @ Ballroom A
Posters and Reception
Oral
Tue Mar 03 06:00 AM -- 06:25 AM (PST) @ Ballroom A
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning
In ML programming models and abstractions & ML applied to systems
Ameer Haj-Ali · Qijing (Jenny) Huang · John Xiang · William Moses · Krste Asanovic · John Wawrzynek · Ion Stoica
Oral
Tue Mar 03 06:25 AM -- 06:50 AM (PST) @ Ballroom A
Automatically batching control-intensive programs for modern accelerators
In ML programming models and abstractions & ML applied to systems
Alexey Radul · Brian Patton · Dougal Maclaurin · Matthew Hoffman · Rif A. Saurous
Oral
Tue Mar 03 06:50 AM -- 07:15 AM (PST) @ Ballroom A
Predictive Precompute with Recurrent Neural Networks
In ML programming models and abstractions & ML applied to systems
Hanson Wang · Zehui Wang · Yuanyuan Ma
Break
Tue Mar 03 07:00 AM -- 08:00 AM (PST) @ Ballroom B
Breakfast and Registration
Oral
Tue Mar 03 07:15 AM -- 07:40 AM (PST) @ Ballroom A
Sense & Sensitivities: The Path to General-Purpose Algorithmic Differentiation
In ML programming models and abstractions & ML applied to systems
Mike Innes
Oral
Tue Mar 03 07:40 AM -- 08:05 AM (PST) @ Ballroom A
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices
In ML programming models and abstractions & ML applied to systems
Byung Hoon Ahn · Jinwon Lee · Jamie Menjay Lin · Hsin-Pai Cheng · Jilei Hou · Hadi Esmaeilzadeh
Oral
Tue Mar 03 08:30 AM -- 08:55 AM (PST) @ Ballroom A
Fine-Grained GPU Sharing Primitives for Deep Learning Applications
In Efficient inference and model serving
Peifeng Yu · Mosharaf Chowdhury
Oral
Tue Mar 03 08:55 AM -- 09:20 AM (PST) @ Ballroom A
Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc
In Efficient inference and model serving
Zhihao Jia · Sina Lin · Mingyu Gao · Matei Zaharia · Alex Aiken
Oral
Tue Mar 03 09:20 AM -- 09:45 AM (PST) @ Ballroom A
OPTIMUS: OPTImized matrix MUltiplication Structure for Transformer neural network accelerator
In Efficient inference and model serving
Junki Park · Hyunsung Yoon · Daehyun Ahn · Jungwook Choi · Jae-Joon Kim
Oral
Tue Mar 03 09:45 AM -- 10:10 AM (PST) @ Ballroom A
PoET-BiN: Power Efficient Tiny Binary Neurons
In Efficient inference and model serving
Sivakumar Chidambaram · Pierre Langlois · Jean-Pierre David
Break
Tue Mar 03 10:05 AM -- 10:30 AM (PST) @ Ballroom B
Coffee Break
Invited Talk
Tue Mar 03 11:30 AM -- 12:30 PM (PST) @ Ballroom A
The Emerging Role of Cryptography in Trustworthy AI
Shafi Goldwasser
[ Video] 
Break
Tue Mar 03 12:10 PM -- 01:30 PM (PST) @ Ballroom B + C
Lunch will be provided
Oral
Tue Mar 03 12:30 PM -- 12:55 PM (PST) @ Ballroom A
Memory-Driven Mixed Low Precision Quantization for Enabling Deep Network Inference on Microcontrollers
In Quantization of deep neural networks
Manuele Rusci · Alessandro Capotondi · Luca Benini
Oral
Tue Mar 03 12:55 PM -- 01:20 PM (PST) @ Ballroom A
Trained Quantization Thresholds for Accurate and Efficient Fixed-Point Inference of Deep Neural Networks
In Quantization of deep neural networks
Sambhav Jain · Albert Gural · Michael Wu · Chris Dick
Oral
Tue Mar 03 01:20 PM -- 01:45 PM (PST) @ Ballroom A
Riptide: Fast End-to-End Binarized Neural Networks
In Quantization of deep neural networks
Joshua Fromm · Meghan Cowan · Matthai Philipose · Luis Ceze · Shwetak Patel
Oral
Tue Mar 03 01:45 PM -- 02:10 PM (PST) @ Ballroom A
Searching for Winograd-aware Quantized Networks
In Quantization of deep neural networks
Javier Fernandez-Marques · Paul Whatmough · Andrew Mundy · Matthew Mattina
Oral
Tue Mar 03 02:30 PM -- 02:55 PM (PST) @ Ballroom A
Blink: Fast and Generic Collectives for Distributed ML
In Efficient Model Training 2
Guanhua Wang · Shivaram Venkataraman · Amar Phanishayee · Nikhil Devanur · Jorgen Thelin · Ion Stoica
Oral
Tue Mar 03 02:55 PM -- 03:20 PM (PST) @ Ballroom A
A Systematic Methodology for Analysis of Deep Learning Hardware and Software Platforms
In Efficient Model Training 2
Yu Wang · Gu-Yeon Wei · David Brooks
Oral
Tue Mar 03 03:20 PM -- 03:45 PM (PST) @ Ballroom A
MotherNets: Rapid Deep Ensemble Learning
In Efficient Model Training 2
Abdul Wasay · Brian Hentschel · Yuze Liao · Sanyuan Chen · Stratos Idreos
Oral
Tue Mar 03 03:45 PM -- 04:10 PM (PST) @ Ballroom A
MLPerf Training Benchmark
In Efficient Model Training 2
Peter Mattson · Christine Cheng · Gregory Diamos · Cody Coleman · Paulius Micikevicius · David Patterson · Hanlin Tang · Gu-Yeon Wei · Peter Bailis · Victor Bittorf · David Brooks · Dehao Chen · Debo Dutta · Udit Gupta · Kim Hazelwood · Andy Hock · Xinyuan Huang · Daniel Kang · David Kanter · Naveen Kumar · Jeffery Liao · Deepak Narayanan · Tayo Oguntebi · Gennady Pekhimenko · Lillian Pentecost · Vijay Janapa Reddi · Taylor Robie · Tom St John · Carole-Jean Wu · Lingjie Xu · Cliff Young · Matei Zaharia
Break
Tue Mar 03 04:10 PM -- 04:30 PM (PST)
Coffee Break
Break
Tue Mar 03 06:10 PM -- 06:15 PM (PST) @ Ballroom A
Closing Remarks
Break
Wed Mar 04 07:00 AM -- 08:00 AM (PST) @ Ballroom B
Breakfast and Registration
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 3 Room 6
Benchmarking Machine Learning Workloads on Emerging Hardware
Tom St John · Murali Emani
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 3 Room 8
Resource-Constrained Machine Learning (ReCoML 2020)
Yaniv Ben Itzhak · Nina Narodytska · Christopher Aberger
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 3 Room 5
MLOps Systems
Debo Dutta · Matei Zaharia · Ce Zhang
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 3 Room 10
CANCELED: Automated Machine Learning For Networks and Distributed Systems
Behnaz Arzani · Bita Darvish Rouhani
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 3 Room 9
Software-Hardware Codesign for Machine Learning Workloads
Ritwik Gupta · John Wohlbier · Tze Meng Low · Jeffrey Vetter · Natalia Vassilieva
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Level 1 Room 3
SARA: Secure and Resilient Autonomy
Pradip Bose · Nandhini Chandramoorthy · Augusto Vega · Karthik Swaminathan
Workshop
Wed Mar 04 07:00 AM -- 03:30 PM (PST) @ Ballroom A
On-Device Intelligence
Vikas Chandra · Pete Warden · Ganesh Venkatesh · Yingyan Lin
Break
Wed Mar 04 10:00 AM -- 10:30 AM (PST) @ Ballroom B + C
Coffee Break
Break
Wed Mar 04 03:30 PM -- 04:00 PM (PST) @ Ballroom B + C
Coffee Break