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ORCIDIISWC 2022: Austin, TX, USA
- IEEE International Symposium on Workload Characterization, IISWC 2022, Austin, TX, USA, November 6-8, 2022. IEEE 2022, ISBN 978-1-6654-8798-6
- Cesar Gomes, Xuesi Chen, Mark Hempstead
:
PInTE: Probabilistic Induction of Theft Evictions. 1-13 - Ondrej Sýkora, Phitchaya Mangpo Phothilimthana, Charith Mendis, Amir Yazdanbakhsh:
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation. 14-26 - Weixi Zhu, Guilherme Cox, Ján Veselý, Mark Hairgrove, Alan L. Cox, Scott Rixner:
UVM Discard: Eliminating Redundant Memory Transfers for Accelerators. 27-38 - Ignacio Laguna, Tanmay Tirpankar, Xinyi Li, Ganesh Gopalakrishnan:
FPChecker: Floating-Point Exception Detection Tool and Benchmark for Parallel and Distributed HPC. 39-50 - Eduardo José Gómez-Hernández, Juan M. Cebrian, Stefanos Kaxiras, Alberto Ros:
Splash-4: A Modern Benchmark Suite with Lock-Free Constructs. 51-64 - Francesco Peverelli, Davide Conficconi, Davide Basilio Bartolini, Alberto Scolari, Marco Domenico Santambrogio:
Characterizing Molecular Dynamics Simulation on Commodity Platforms. 65-78 - Kiran Seshadri, Berkin Akin, James Laudon, Ravi Narayanaswami, Amir Yazdanbakhsh:
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks. 79-91 - Jaewan Choi, Hailong Li, Byeongho Kim, Seunghwan Hwang, Jung Ho Ahn:
Accelerating Transformer Networks through Recomposing Softmax Layers. 92-103 - Hailong Li, Jaewan Choi, Jung Ho Ahn:
A Slice and Dice Approach to Accelerate Compound Sparse Attention on GPU. 104-116 - Young Geun Kim, Carole-Jean Wu:
FedGPO: Heterogeneity-Aware Global Parameter optimization for Efficient Federated Learning. 117-129 - Hanqiu Chen, Yahya Alhinai, Yihan Jiang, Eunjee Na, Cong Hao:
Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPU. 130-145 - Taha Tekdogan, Serkan Göktas, Ayse Yilmazer-Metin:
gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs. 146-159 - Xin Huang, Jongryool Kim, Bradley Rees, Chul-Ho Lee:
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass. 160-170 - Diego Moura, Daniel Mossé, Vinicius Petrucci:
Performance Characterization of AutoNUMA Memory Tiering on Graph Analytics. 171-184 - Jhe-Yu Liou, Muaaz Awan, Steven A. Hofmeyr, Stephanie Forrest, Carole-Jean Wu:
Understanding the Power of Evolutionary Computation for GPU Code Optimization. 185-198 - Aninda Manocha, Zi Yan, Esin Tureci, Juan L. Aragón, David W. Nellans, Margaret Martonosi:
The Implications of Page Size Management on Graph Analytics. 199-214 - Qiang Zou, Bo Mao:
Revisiting Temporal Storage I/O Behaviors of Smartphone Applications: Analysis and Synthesis. 215-227 - Wenwen Wang:
How Far We've Come - A Characterization Study of Standalone WebAssembly Runtimes. 228-241 - Sungjae Lee, Jaeil Hwang, Kyungyong Lee:
SpotLake: Diverse Spot Instance Dataset Archive Service. 242-255 - Raven Szewczyk, Kimberley Stonehouse, Antonio Barbalace, Tom Spink:
Leaps and bounds: Analyzing WebAssembly's performance with a focus on bounds checking. 256-268 - Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna:
Demystifying Map Space Exploration for NPUs. 269-281 - Xiuhong Li, Shengen Yan, Lijuan Jiang, Ping Xu, Jinming Ma, Xingcheng Zhang, Dahua Lin:
LongTail-Bench: A Benchmark Suite for Domain-Specific Operators in Deep Learning. 282-295 - Suchita Pati, Shaizeen Aga, Nuwan Jayasena, Matthew D. Sinclair:
Demystifying BERT: System Design Implications. 296-309
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