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All Projects → SJTU-ReArch-Group → Paper-Reading-List

SJTU-ReArch-Group / Paper-Reading-List

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ReArch Group Paper Reading List

 

Seminars

Spring 2021

Date Paper Title Presenter Notes
03.01 Training for Multi-resolution Inference Using Reusable Quantization Terms Cong Guo
03.08 Toward Efficient Interactions between Python and Native Libraries Yuxian Qiu
03.15 SpAtten: Efficient Natural Language Processing Yue Guan
03.22 X-Stream: Edge-centric Graph Processing using Streaming Partitions Zhihui Zhang
03.29 Loop Nested Optimization, Polyhedral Model and Micro-2020 Best Paper (Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data) Zihan Liu Slides
04.12 Defensive Approximation: Securing CNNs using Approximate Computing Yakai Wang Related Work
05.17 Commutative Data Reordering: A New Technique to Reduce Data Movement Energy on Sparse Inference Workloads Yangjie Zhou ISCA 2020
05.31 Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture Zhihui Zhang VLDB 2021
06.07 DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Yue Guan NeurIPS 2021

Summer 2021

Date Paper Title Presenter Notes
07.14 AKG: automatic kernel generation for neural processing units using polyhedral transformations (PLDI 2021) Yuxian Qiu Slides
07.21 Floating-Point Format and Quantization for Deep Learning Computation Cong Guo
07.28 P-OPT: Practical Optimal Cache Replacement for Graph Analytics Yangjie Zhou Slides
08.04 Rubik: A Hierarchical Architecture for Efficient Graph Neural Network Training Zhihui Zhang
08.11 A Useful Tool CKA: Similarity of Neural Network Representations Revisited and It's application: Uncovering How Neural Network Representations Vary with Width and Depth Zhengyi Li Slides
08.18 Ansor: Generating High-Performance Tensor Programs for Deep Learning Zihan Liu Slides

Fall 2021

Date Paper Title Presenter Notes
10.11 Adaptive numeric type for DNN quantization Cong Guo
10.18 Compiling Graph Applications for GPUs with GraphIt Yangjie Zhou Slides
11.01 TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation Zihan Liu Slides
11.08 Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity Zhengyi Li Slides (code: zdea)
11.22 Dynamic Tensor Rematerialization
Checkmate: Breaking The Memory Wall with Optimal Tensor Rematerialization		 Yue Guan Slides
Slides
11.29 GraphPulse: An Event-Driven Hardware Accelerator for Asynchronous Graph Processing Zhihui Zhang Presentation
12.06 CheckFreq: Frequent, Fine-Grained DNN Checkpointing Guandong Lu Slides
12.13 PipeDream: generalized pipeline parallelism for DNN training Runzhe Chen Slides
12.20 Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters Yakai Wang Slides

Spring 2022

Date Paper Title Presenter Notes
3.10 Speculation Attack: Meltdown, Spectre, Pinned-Loads Zihan Liu Slides

DNN Architecture

Link

 

Deep Learning Compiler

List Contributed by Zihan Liu

 

Past Architecture Papers

List Contributed by Jingwen Leng

 

Reading List From Other Groups

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