(131 events)   Timezone: »  
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Symposium
Mon Apr 05 08:30 AM -- 05:00 PM (PDT) @ Virtual
Chips and Compilers Symposium
Mu Li · Tianqi Chen
Remarks
Tue Apr 06 08:00 AM -- 08:15 AM (PDT)
Opening Remarks
Alex Dimakis · Ion Stoica · Alexander Smola
Invited Talk
Tue Apr 06 08:20 AM -- 09:10 AM (PDT)
Directions for Deep Learning Hardware
William Dally
Break
Tue Apr 06 09:10 AM -- 09:30 AM (PDT)
Break
Oral
Tue Apr 06 09:30 AM -- 09:50 AM (PDT)
ModularNAS: Towards Modularized and Reusable Neural Architecture Search
Yunfeng Lin · Guilin Li · Xing Zhang · Weinan Zhang · Bo Chen · Ruiming Tang · Zhenguo Li · Jiashi Feng · Yong Yu
Oral
Tue Apr 06 09:50 AM -- 10:10 AM (PDT)
Fluid: Resource-aware Hyperparameter Tuning Engine
Peifeng Yu · Jiachen Liu · Mosharaf Chowdhury
Oral
Tue Apr 06 10:10 AM -- 10:30 AM (PDT)
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
Colby Banbury · Chuteng Zhou · Igor Fedorov · Ramon Matas · Urmish Thakker · Dibakar Gope · Vijay Janapa Reddi · Matthew Mattina · Paul Whatmough
Oral
Tue Apr 06 10:30 AM -- 10:50 AM (PDT)
Characterizing and Taming Model Instability Across Edge Devices
Eyal Cidon · Evgenya Pergament · Zain Asgar · Asaf Cidon · Sachin Katti
Break
Tue Apr 06 10:50 AM -- 11:10 AM (PDT)
Break
Oral
Tue Apr 06 11:10 AM -- 11:30 AM (PDT)
Cortex: A Compiler for Recursive Deep Learning Models
Pratik Fegade · Tianqi Chen · Phillip Gibbons · Todd Mowry
Oral
Tue Apr 06 11:30 AM -- 11:50 AM (PDT)
A Deep Learning Based Cost Model for Automatic Code Optimization
Riyadh Baghdadi · Massinissa Merouani · Mohamed-Hicham LEGHETTAS · Kamel Abdous · Taha Arbaoui · Karima BENATCHBA · Saman amarasinghe
Oral
Tue Apr 06 11:50 AM -- 12:10 PM (PDT)
Learning Fitness Functions for Machine Programming
Shantanu Mandal · Todd Anderson · Javier Turek · Justin Gottschlich · Shengtian Zhou · Abdullah Muzahid
Oral
Tue Apr 06 12:10 PM -- 12:30 PM (PDT)
CODE: Compiler-based Neuron-aware Ensemble training
Ettore M. G. Trainiti · Thanapon Noraset · David Demeter · Doug Downey · Simone Campanoni
Break
Tue Apr 06 12:30 PM -- 01:30 PM (PDT)
Lunch break
Oral
Tue Apr 06 01:30 PM -- 01:50 PM (PDT)
Pufferfish: Communication-efficient Models At No Extra Cost
Hongyi Wang · Saurabh Agarwal · Dimitris Papailiopoulos
Oral
Tue Apr 06 01:50 PM -- 02:10 PM (PDT)
In-network Aggregation for Shared Machine Learning Clusters
Nadeen Gebara · Manya Ghobadi · Costa Paolo
Oral
Tue Apr 06 02:10 PM -- 02:30 PM (PDT)
Data Movement Is All You Need: A Case Study on Optimizing Transformers
Andrei Ivanov · Nikoli Dryden · Tal Ben-Nun · Shigang Li · Torsten Hoefler
Oral
Tue Apr 06 02:30 PM -- 02:50 PM (PDT)
Learning on Distributed Traces for Data Center Storage Systems
Giulio Zhou · Martin Maas
Break
Tue Apr 06 02:50 PM -- 03:20 PM (PDT)
Break
Oral
Tue Apr 06 03:20 PM -- 03:40 PM (PDT)
TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems
Robert David · Jared Duke · Advait Jain · Vijay Janapa Reddi · Nat Jeffries · Jian Li · Nick Kreeger · Ian Nappier · Meghna Natraj · Tiezhen Wang · Pete Warden · Rocky Rhodes · Rocky Rhodes
Oral
Tue Apr 06 03:40 PM -- 04:00 PM (PDT)
Scaling Distributed Training with Adaptive Summation
Saeed Maleki · Madan Musuvathi · Todd Mytkowicz · Olli Saarikivi · Tianju Xu · Vadim Eksarevskiy · Jaliya Ekanayake · Emad Barsoum
Oral
Tue Apr 06 04:00 PM -- 04:20 PM (PDT)
PipeMare: Asynchronous Pipeline Parallel DNN Training
Bowen Yang · Jian Zhang · Jonathan Li · Christopher Re · Christopher Aberger · Christopher De Sa
Oral
Tue Apr 06 04:20 PM -- 04:40 PM (PDT)
EXPLORING THE LIMITS OF CONCURRENCY IN ML TRAINING ON GOOGLE TPUS
Sameer Kumar · Yu Wang · Cliff Young · James Bradbury · Naveen Kumar · Dehao Chen · Andy Swing
Oral
Tue Apr 06 04:40 PM -- 05:00 PM (PDT)
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models
Chunxing Yin · Bilge Acun · Carole-Jean Wu · Xing Liu
Poster
Tue Apr 06 05:00 PM (PDT)
Fluid: Resource-aware Hyperparameter Tuning Engine
Peifeng Yu · Jiachen Liu · Mosharaf Chowdhury
Poster
Tue Apr 06 05:00 PM (PDT) @ Virtual
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models
Chunxing Yin · Bilge Acun · Carole-Jean Wu · Xing Liu
Poster
Tue Apr 06 05:00 PM (PDT)
A Deep Learning Based Cost Model for Automatic Code Optimization
Riyadh Baghdadi · Massinissa Merouani · Mohamed-Hicham LEGHETTAS · Kamel Abdous · Taha Arbaoui · Karima BENATCHBA · Saman Amarasinghe
Poster
Tue Apr 06 05:00 PM (PDT)
Learning Fitness Functions for Machine Programming
Shantanu Mandal · Todd Anderson · Javier Turek · Justin Gottschlich · Shengtian Zhou · Abdullah Muzahid
Poster
Tue Apr 06 05:00 PM (PDT) @ Virtual
Cortex: A Compiler for Recursive Deep Learning Models
Pratik Fegade · Tianqi Chen · Phillip Gibbons · Todd Mowry
Poster
Tue Apr 06 05:00 PM (PDT)
Learning on Distributed Traces for Data Center Storage Systems
Giulio Zhou · Martin Maas
Poster
Tue Apr 06 05:00 PM (PDT)
Pufferfish: Communication-efficient Models At No Extra Cost
Hongyi Wang · Saurabh Agarwal · Dimitris Papailiopoulos
Poster
Tue Apr 06 05:00 PM (PDT) @ Virtual
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
Colby Banbury · Chuteng Zhou · Igor Fedorov · Ramon Matas · Urmish Thakker · Dibakar Gope · Vijay Janapa Reddi · Matthew Mattina · Paul Whatmough
Poster
Tue Apr 06 05:00 PM (PDT)
Characterizing and Taming Model Instability Across Edge Devices
Eyal Cidon · Evgenya Pergament · Zain Asgar · Asaf Cidon · Sachin Katti
Poster
Tue Apr 06 05:00 PM (PDT)
PipeMare: Asynchronous Pipeline Parallel DNN Training
Bowen Yang · Jian Zhang · Jonathan Li · Christopher Re · Christopher Aberger · Christopher De Sa
Poster
Tue Apr 06 05:00 PM (PDT)
Scaling Distributed Training with Adaptive Summation
Saeed Maleki · Madan Musuvathi · Todd Mytkowicz · Olli Saarikivi · Tianju Xu · Vadim Eksarevskiy · Jaliya Ekanayake · Emad Barsoum
Poster
Tue Apr 06 05:00 PM (PDT)
ModularNAS: Towards Modularized and Reusable Neural Architecture Search
Yunfeng Lin · Guilin Li · Xing Zhang · Weinan Zhang · Bo Chen · Ruiming Tang · Zhenguo Li · Jiashi Feng · Yong Yu
Poster
Tue Apr 06 05:00 PM (PDT)
Data Movement Is All You Need: A Case Study on Optimizing Transformers
Andrei Ivanov · Nikoli Dryden · Tal Ben-Nun · Shigang Li · Torsten Hoefler
Poster
Tue Apr 06 05:00 PM (PDT)
EXPLORING THE LIMITS OF CONCURRENCY IN ML TRAINING ON GOOGLE TPUS
Sameer Kumar · Yu Wang · Cliff Young · James Bradbury · Naveen Kumar · Dehao Chen · Andy Swing
Poster
Tue Apr 06 05:00 PM (PDT) @ Virtual
In-network Aggregation for Shared Machine Learning Clusters
Nadeen Gebara · Manya Ghobadi · Costa Paolo
Poster
Tue Apr 06 05:00 PM (PDT)
TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems
Robert David · Jared Duke · Advait Jain · Vijay Janapa Reddi · Nat Jeffries · Jian Li · Nick Kreeger · Ian Nappier · Meghna Natraj · Tiezhen Wang · Pete Warden · Rocky Rhodes · Rocky Rhodes
Poster
Tue Apr 06 05:00 PM (PDT)
CODE: Compiler-based Neuron-aware Ensemble training
Ettore M. G. Trainiti · Thanapon Noraset · David Demeter · Doug Downey · Simone Campanoni
Session
Tue Apr 06 05:00 PM (PDT)
Poster Session 1
Invited Talk
Wed Apr 07 08:00 AM -- 08:50 AM (PDT)
Trustworthy AI
Jeannette Wing
Break
Wed Apr 07 08:50 AM -- 09:10 AM (PDT)
Break
Oral
Wed Apr 07 09:10 AM -- 09:30 AM (PDT)
An Efficient Statistical-based Gradient Compression Technique for Distributed Training Systems
Ahmed M. Abdelmoniem · Ahmed Elzanaty · Mohamed-Slim Alouini · Marco Canini
Oral
Wed Apr 07 09:30 AM -- 09:50 AM (PDT)
Adaptive Gradient Communication via Critical Learning Regime Identification
Saurabh Agarwal · Hongyi Wang · Kangwook Lee · Shivaram Venkataraman · Dimitris Papailiopoulos
Oral
Wed Apr 07 09:50 AM -- 10:10 AM (PDT)
Don't Forget to Sign the Gradients!
Omid Aramoon · Pin-Yu Chen · Gang Qu
Oral
Wed Apr 07 10:10 AM -- 10:30 AM (PDT)
Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators
Hamzah Abdelaziz · ali shafiee · Jong Hoon Shin · Ardavan Pedram · Joseph Hassoun
Oral
Wed Apr 07 10:30 AM -- 10:50 AM (PDT)
Bit Error Robustness for Energy-Efficient DNN Accelerators
David Stutz · Nandhini Chandramoorthy · Matthias Hein · Bernt Schiele
Break
Wed Apr 07 10:50 AM -- 11:10 AM (PDT)
Break - Visit the
Oral
Wed Apr 07 11:10 AM -- 11:30 AM (PDT)
RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads
James Gleeson · Srivatsan Krishnan · Moshe Gabel · Vijay Janapa Reddi · Eyal de Lara · Gennady Pekhimenko
Oral
Wed Apr 07 11:30 AM -- 11:50 AM (PDT)
A Learned Performance Model for Tensor Processing Units
Sam Kaufman · Phitchaya Phothilimthana · Yanqi Zhou · Charith Mendis · Sudip Roy · Amit Sabne · Mike Burrows
Oral
Wed Apr 07 11:50 AM -- 12:10 PM (PDT)
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier · Pierre Delaunay · Mirko Bronzi · Assya Trofimov · Brennan Nichyporuk · Justin Szeto · Nazanin Mohammadi Sepahvand · Edward Raff · Kanika Madan · Vikram Voleti · Samira Ebrahimi Kahou · Vincent Michalski · Tal Arbel · Chris Pal · Gael Varoquaux · Pascal Vincent
Oral
Wed Apr 07 12:10 PM -- 12:30 PM (PDT)
Larq Compute Engine: Design, Benchmark and Deploy State-of-the-Art Binarized Neural Networks
Tom Bannink · Adam Hillier · Lukas Geiger · Tim de Bruin · Leon Overweel · Jelmer Neeven · Koen Helwegen
Break
Wed Apr 07 12:30 PM -- 01:30 PM (PDT)
Lunch Break / Visit the
Oral
Wed Apr 07 01:30 PM -- 01:50 PM (PDT)
IOS: Inter-Operator Scheduler for CNN Acceleration
Yaoyao Ding · Ligeng Zhu · Zhihao Jia · Gennady Pekhimenko · Song Han
Oral
Wed Apr 07 01:50 PM -- 02:10 PM (PDT)
Value Learning for Throughput Optimization of Deep Learning Workloads
Benoit Steiner · Chris Cummins · Horace He · Hugh Leather
Oral
Wed Apr 07 02:10 PM -- 02:30 PM (PDT)
ByzShield: An Efficient and Robust System for Distributed Training
Konstantinos Konstantinidis · Aditya Ramamoorthy
Oral
Wed Apr 07 02:30 PM -- 02:50 PM (PDT)
FirePlace: Placing Firecraker Virtual Machines with Hindsight Imitation
Bharathan Balaji · Christopher Kakovitch · Balakrishnan Narayanaswamy
Break
Wed Apr 07 02:50 PM -- 03:20 PM (PDT)
Break - Visit the
Oral
Wed Apr 07 03:20 PM -- 03:40 PM (PDT)
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Haichen Shen · Jared Roesch · Zhi Chen · Wei Chen · Yong Wu · Mu Li · Vin Sharma · Zachary Tatlock · Yida Wang
Oral
Wed Apr 07 03:40 PM -- 04:00 PM (PDT)
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions
Wenqi Jiang · Zhenhao He · Shuai Zhang · Thomas B. Preußer · Kai Zeng · Liang Feng · Jiansong Zhang · Tongxuan Liu · Yong Li · Jingren Zhou · Ce Zhang · Gustavo Alonso
Oral
Wed Apr 07 04:00 PM -- 04:20 PM (PDT)
VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference
Steve Dai · Rangha Venkatesan · Mark Ren · Brian Zimmer · William Dally · Brucek Khailany
Oral
Wed Apr 07 04:20 PM -- 04:40 PM (PDT)
Accelerate Inference of CNNs for Video Analysis While Preserving Exactness Exploiting Activation Sparsity
Toshiaki Wakatsuki · Sekitoshi Kanai · Yasuhiro Fujiwara
Oral
Wed Apr 07 04:40 PM -- 05:00 PM (PDT)
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data
Guanhua Wang · Zhuang Liu · Brandon Hsieh · Siyuan Zhuang · Joseph Gonzalez · Trevor Darrell · Ion Stoica
Poster
Wed Apr 07 05:00 PM (PDT)
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier · Pierre Delaunay · Mirko Bronzi · Assya Trofimov · Brennan Nichyporuk · Justin Szeto · Nazanin Mohammadi Sepahvand · Edward Raff · Kanika Madan · Vikram Voleti · Samira Ebrahimi Kahou · Vincent Michalski · Tal Arbel · Chris Pal · Gael Varoquaux · Pascal Vincent
Poster
Wed Apr 07 05:00 PM (PDT)
A Learned Performance Model for Tensor Processing Units
Sam Kaufman · Phitchaya Phothilimthana · Yanqi Zhou · Charith Mendis · Sudip Roy · Amit Sabne · Mike Burrows
Poster
Wed Apr 07 05:00 PM (PDT)
An Efficient Statistical-based Gradient Compression Technique for Distributed Training Systems
Ahmed M. Abdelmoniem · Ahmed Elzanaty · Mohamed-Slim Alouini · Marco Canini
Poster
Wed Apr 07 05:00 PM (PDT)
Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators
Hamzah Abdelaziz · ali shafiee · Jong Hoon Shin · Ardavan Pedram · Joseph Hassoun
Poster
Wed Apr 07 05:00 PM (PDT)
Larq Compute Engine: Design, Benchmark and Deploy State-of-the-Art Binarized Neural Networks
Tom Bannink · Adam Hillier · Lukas Geiger · Tim de Bruin · Leon Overweel · Jelmer Neeven · Koen Helwegen
Poster
Wed Apr 07 05:00 PM (PDT)
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions
Wenqi Jiang · Zhenhao He · Shuai Zhang · Thomas B. Preußer · Kai Zeng · Liang Feng · Jiansong Zhang · Tongxuan Liu · Yong Li · Jingren Zhou · Ce Zhang · Gustavo Alonso
Poster
Wed Apr 07 05:00 PM (PDT)
FirePlace: Placing Firecraker Virtual Machines with Hindsight Imitation
Bharathan Balaji · Christopher Kakovitch · Balakrishnan Narayanaswamy
Poster
Wed Apr 07 05:00 PM (PDT)
ByzShield: An Efficient and Robust System for Distributed Training
Konstantinos Konstantinidis · Aditya Ramamoorthy
Poster
Wed Apr 07 05:00 PM (PDT)
Value Learning for Throughput Optimization of Deep Learning Workloads
Benoit Steiner · Chris Cummins · Horace He · Hugh Leather
Poster
Wed Apr 07 05:00 PM (PDT) @ Virtual
VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference
Steve Dai · Rangha Venkatesan · Mark Ren · Brian Zimmer · William Dally · Brucek Khailany
Poster
Wed Apr 07 05:00 PM (PDT)
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Haichen Shen · Jared Roesch · Zhi Chen · Wei Chen · Yong Wu · Mu Li · Vin Sharma · Zachary Tatlock · Yida Wang
Poster
Wed Apr 07 05:00 PM (PDT) @ Virtual
Don't Forget to Sign the Gradients!
Omid Aramoon · Pin-Yu Chen · Gang Qu
Poster
Wed Apr 07 05:00 PM (PDT) @ Virtual
Bit Error Robustness for Energy-Efficient DNN Accelerators
David Stutz · Nandhini Chandramoorthy · Matthias Hein · Bernt Schiele
Poster
Wed Apr 07 05:00 PM (PDT)
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data
Guanhua Wang · Zhuang Liu · Brandon Hsieh · Siyuan Zhuang · Joseph Gonzalez · Trevor Darrell · Ion Stoica
Poster
Wed Apr 07 05:00 PM (PDT)
RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads
James Gleeson · Srivatsan Krishnan · Moshe Gabel · Vijay Janapa Reddi · Eyal de Lara · Gennady Pekhimenko
Poster
Wed Apr 07 05:00 PM (PDT)
Adaptive Gradient Communication via Critical Learning Regime Identification
Saurabh Agarwal · Hongyi Wang · Kangwook Lee · Shivaram Venkataraman · Dimitris Papailiopoulos
Poster
Wed Apr 07 05:00 PM (PDT)
Accelerate Inference of CNNs for Video Analysis While Preserving Exactness Exploiting Activation Sparsity
Toshiaki Wakatsuki · Sekitoshi Kanai · Yasuhiro Fujiwara
Poster
Wed Apr 07 05:00 PM (PDT) @ Virtual
IOS: Inter-Operator Scheduler for CNN Acceleration
Yaoyao Ding · Ligeng Zhu · Zhihao Jia · Gennady Pekhimenko · Song Han
Session
Wed Apr 07 05:00 PM (PDT)
Poster Session 2
Invited Talk
Thu Apr 08 08:00 AM -- 08:50 AM (PDT)
Machine Learning in Science: Applications, Algorithms and Architectures
Kathy Yelick
Break
Thu Apr 08 08:50 AM -- 09:10 AM (PDT)
Break - Visit the
Oral
Thu Apr 08 09:10 AM -- 09:30 AM (PDT)
Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick
Isak Edo Vivancos · Sayeh Sharify · Daniel Ly-Ma · Ameer Abdelhadi · Ciaran Bannon · Milos Nikolic · Mostafa Mahmoud · Alberto Delmas Lascorz · Gennady Pekhimenko · Andreas Moshovos
Oral
Thu Apr 08 09:30 AM -- 09:50 AM (PDT)
Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models
Shang Wang · Peiming Yang · Yuxuan Zheng · Xin Li · Gennady Pekhimenko
Oral
Thu Apr 08 09:50 AM -- 10:10 AM (PDT)
A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems
Guixiang Ma · Yao Xiao · Theodore Willke · Nesreen Ahmed · Shahin Nazarian · Paul Bogdan
Oral
Thu Apr 08 10:10 AM -- 10:30 AM (PDT)
Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More
Shabnam Daghaghi · Nicholas Meisburger · Mengnan Zhao · Anshumali Shrivastava
Oral
Thu Apr 08 10:30 AM -- 10:50 AM (PDT)
Scaling Polyhedral Neural Network Verification on GPUs
Christoph Müller · François Serre · Gagandeep Singh · Markus Püschel · Martin Vechev
Break
Thu Apr 08 10:50 AM -- 11:10 AM (PDT)
Break - Visit the
Oral
Thu Apr 08 11:10 AM -- 11:30 AM (PDT)
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection
Yue Zhao · Xiyang Hu · Cheng Cheng · Cong Wang · Changlin Wan · Wen Wang · Jianing Yang · Haoping Bai · Zheng Li · Cao Xiao · Yunlong Wang · Zhi Qiao · Jimeng Sun · Leman Akoglu
Oral
Thu Apr 08 11:30 AM -- 11:50 AM (PDT)
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy
Lucas Liebenwein · Cenk Baykal · Brandon Carter · David Gifford · Daniela Rus
Oral
Thu Apr 08 11:50 AM -- 12:10 PM (PDT)
Equality Saturation for Tensor Graph Superoptimization
Yichen Yang · Phitchaya Phothilimthana · Yisu Wang · Max Willsey · Sudip Roy · Jacques Pienaar
Oral
Thu Apr 08 12:10 PM -- 12:30 PM (PDT)
Doping: A technique for Extreme Compression of LSTM Models using Sparse Structured Additive Matrices
Urmish Thakker · Paul Whatmough · ZHIGANG LIU · Matthew Mattina · Jesse Beu
Break
Thu Apr 08 12:30 PM -- 01:30 PM (PDT)
Lunch Break / Visit the
Oral
Thu Apr 08 01:30 PM -- 01:50 PM (PDT)
Swift for TensorFlow: A portable, flexible platform for deep learning
Brennan Saeta · Denys Shabalin
Oral
Thu Apr 08 01:50 PM -- 02:10 PM (PDT)
Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training
Nathalie Rauschmayr · Vikas Kumar · Rahul Huilgol · Andrea Olgiati · Satadal Bhattacharjee · Nihal Harish · Vandana Kannan · Amol Lele · Anirudh Acharya · Jared Nielsen · Lakshmi Ramakrishnan · Ishan Bhatt · Kohen Chia · Neelesh Dodda · Zhihan Li · Jiacheng Gu · Miyoung Choi · Balajee Nagarajan · Jeffrey Geevarghese · Denis Davydenko · Sifei Li · Lu Huang · Edward Kim · Tyler Hill · Krishnaram Kenthapadi
Oral
Thu Apr 08 02:10 PM -- 02:30 PM (PDT)
FLAML: A Fast and Lightweight AutoML Library
Chi Wang · Qingyun Wu · Markus Weimer · Erkang Zhu
Oral
Thu Apr 08 02:30 PM -- 02:50 PM (PDT)
To Bridge Neural Network Design and Real-World Performance: A Behaviour Study for Neural Networks
Xiaohu Tang · Shihao Han · Li Lyna Zhang · Ting Cao · Yunxin Liu
Break
Thu Apr 08 02:50 PM -- 03:20 PM (PDT)
Break - Visit the
Oral
Thu Apr 08 03:20 PM -- 03:40 PM (PDT)
Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters
Shaohuai Shi · Xianhao Zhou · Shutao Song · Xingyao Wang · Zilin Zhu · Xue Huang · Xinan Jiang · Feihu Zhou · Zhenyu Guo · Liqiang Xie · Rui Lan · Xianbin Ouyang · Yan Zhang · Jieqian Wei · Jing Gong · Weiliang Lin · Ping Gao · Peng Meng · Xiaomin Xu · Chenyang Guo · Bo Yang · Zhibo Chen · Yongjian Wu · Xiaowen Chu
Oral
Thu Apr 08 03:40 PM -- 04:00 PM (PDT)
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
Kiwan Maeng · Shivam Bharuka · Isabel Gao · Mark Jeffrey · Vikram Saraph · Bor-Yiing Su · Caroline Trippel · Jiyan Yang · Mike Rabbat · Brandon Lucia · Carole-Jean Wu
Oral
Thu Apr 08 04:00 PM -- 04:20 PM (PDT)
Wavelet: Efficient DNN Training with Tick-Tock Scheduling
Guanhua Wang · Kehan Wang · Kenan Jiang · XIANGJUN LI · Ion Stoica
Oral
Thu Apr 08 04:20 PM -- 04:40 PM (PDT)
Pipelined Backpropagation at Scale: Training Large Models without Batches
Atli Kosson · Vitaliy Chiley · Abhinav Venigalla · Joel Hestness · Urs Koster
Remarks
Thu Apr 08 04:40 PM -- 05:00 PM (PDT)
Closing Remarks
Poster
Thu Apr 08 05:00 PM (PDT) @ Virtual
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
Kiwan Maeng · Shivam Bharuka · Isabel Gao · Mark Jeffrey · Vikram Saraph · Bor-Yiing Su · Caroline Trippel · Jiyan Yang · Mike Rabbat · Brandon Lucia · Carole-Jean Wu
Poster
Thu Apr 08 05:00 PM (PDT) @ Virtual
Pipelined Backpropagation at Scale: Training Large Models without Batches
Atli Kosson · Vitaliy Chiley · Abhinav Venigalla · Joel Hestness · Urs Koster
Poster
Thu Apr 08 05:00 PM (PDT) @ Virtual
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy
Lucas Liebenwein · Cenk Baykal · Brandon Carter · David Gifford · Daniela Rus
Poster
Thu Apr 08 05:00 PM (PDT) @ Virtual
Scaling Polyhedral Neural Network Verification on GPUs
Christoph Müller · François Serre · Gagandeep Singh · Markus Püschel · Martin Vechev
Poster
Thu Apr 08 05:00 PM (PDT)
Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models
Shang Wang · Peiming Yang · Yuxuan Zheng · Xin Li · Gennady Pekhimenko
Poster
Thu Apr 08 05:00 PM (PDT)
To Bridge Neural Network Design and Real-World Performance: A Behaviour Study for Neural Networks
Xiaohu Tang · Shihao Han · Li Lyna Zhang · Ting Cao · Yunxin Liu
Poster
Thu Apr 08 05:00 PM (PDT)
Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More
Shabnam Daghaghi · Nicholas Meisburger · Mengnan Zhao · Anshumali Shrivastava
Poster
Thu Apr 08 05:00 PM (PDT)
Wavelet: Efficient DNN Training with Tick-Tock Scheduling
Guanhua Wang · Kehan Wang · Kenan Jiang · XIANGJUN LI · Ion Stoica
Poster
Thu Apr 08 05:00 PM (PDT)
Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters
Shaohuai Shi · Xianhao Zhou · Shutao Song · Xingyao Wang · Zilin Zhu · Xue Huang · Xinan Jiang · Feihu Zhou · Zhenyu Guo · Liqiang Xie · Rui Lan · Xianbin Ouyang · Yan Zhang · Jieqian Wei · Jing Gong · Weiliang Lin · Ping Gao · Peng Meng · Xiaomin Xu · Chenyang Guo · Bo Yang · Zhibo Chen · Yongjian Wu · Xiaowen Chu
Poster
Thu Apr 08 05:00 PM (PDT)
Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training
Nathalie Rauschmayr · Vikas Kumar · Rahul Huilgol · Andrea Olgiati · Satadal Bhattacharjee · Nihal Harish · Vandana Kannan · Amol Lele · Anirudh Acharya · Jared Nielsen · Lakshmi Ramakrishnan · Ishan Bhatt · Kohen Chia · Neelesh Dodda · Zhihan Li · Jiacheng Gu · Miyoung Choi · Balajee Nagarajan · Jeffrey Geevarghese · Denis Davydenko · Sifei Li · Lu Huang · Edward Kim · Tyler Hill · Krishnaram Kenthapadi
Poster
Thu Apr 08 05:00 PM (PDT)
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection
Yue Zhao · Xiyang Hu · Cheng Cheng · Cong Wang · Changlin Wan · Wen Wang · Jianing Yang · Haoping Bai · Zheng Li · Cao Xiao · Yunlong Wang · Zhi Qiao · Jimeng Sun · Leman Akoglu
Poster
Thu Apr 08 05:00 PM (PDT)
FLAML: A Fast and Lightweight AutoML Library
Chi Wang · Qingyun Wu · Markus Weimer · Erkang Zhu
Poster
Thu Apr 08 05:00 PM (PDT)
Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick
Isak Edo Vivancos · Sayeh Sharify · Daniel Ly-Ma · Ameer Abdelhadi · Ciaran Bannon · Milos Nikolic · Mostafa Mahmoud · Alberto Delmas Lascorz · Gennady Pekhimenko · Andreas Moshovos
Poster
Thu Apr 08 05:00 PM (PDT)
Swift for TensorFlow: A portable, flexible platform for deep learning
Brennan Saeta · Denys Shabalin
Poster
Thu Apr 08 05:00 PM (PDT)
Equality Saturation for Tensor Graph Superoptimization
Yichen Yang · Phitchaya Phothilimthana · Yisu Wang · Max Willsey · Sudip Roy · Jacques Pienaar
Poster
Thu Apr 08 05:00 PM (PDT)
Doping: A technique for Extreme Compression of LSTM Models using Sparse Structured Additive Matrices
Urmish Thakker · Paul Whatmough · ZHIGANG LIU · Matthew Mattina · Jesse Beu
Poster
Thu Apr 08 05:00 PM (PDT)
A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems
Guixiang Ma · Yao Xiao · Theodore Willke · Nesreen Ahmed · Shahin Nazarian · Paul Bogdan
Session
Thu Apr 08 05:00 PM (PDT)
Poster Session 3
Workshop
Fri Apr 09 06:15 AM -- 03:00 PM (PDT)
Personalized Recommendation Systems and Algorithms
Udit Gupta · Carole-Jean Wu · Gu-Yeon Wei · David Brooks
Workshop
Fri Apr 09 07:00 AM -- 03:00 PM (PDT)
2nd On-Device Intelligence Workshop
Paul Whatmough · Vijay Janapa Reddi · Chuteng Zhou · Igor Federov · Matthew Mattina · Pete Warden · Ganesh Venkatesh · Vikas Chandra
Workshop
Fri Apr 09 07:00 AM -- 04:00 PM (PDT)
Workshop of Graph Neural Networks and Systems (GNNSys'21)
Xavier Bresson · Michael Bronstein · Stefanie Jegelka · George Karypis · Petar Veličković · Zheng Zhang
Workshop
Fri Apr 09 07:45 AM -- 04:00 PM (PDT)
SysML4Health: Scalable Systems for ML-driven Analytics in Healthcare
Alexey Tumanov · Jimeng Sun · Tushar Krishna · Vivek Sarkar · Dawn Song
Workshop
Fri Apr 09 08:00 AM -- 05:00 PM (PDT)
Benchmarking Machine Learning Workloads on Emerging Hardware
Tom St John · Murali Emani
Workshop
Fri Apr 09 08:00 AM -- 03:00 PM (PDT)
Journal of Opportunities, Unexpected limitations, Retrospectives, Negative results, and Experiences
Abhishek Gupta · Udit Gupta · Mayoore Jaiswal · Lillian Pentecost · Shagun Sodhani · David Brooks · Joelle Pineau