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ORCIDIISWC 2019: Orlando, FL, USA
- IEEE International Symposium on Workload Characterization, IISWC 2019, Orlando, FL, USA, November 3-5, 2019. IEEE 2019, ISBN 978-1-7281-4045-2
- Priyank Faldu
, Jeff Diamond, Boris Grot:
A Closer Look at Lightweight Graph Reordering. 1-13 - Huanxing Shen, Cong Li:
Detecting Last-Level Cache Contention in Workload Colocation with Meta Learning. 14-23 - Valentin Radu, Kuba Kaszyk, Yuan Wen, Jack Turner, José Cano, Elliot J. Crowley, Björn Franke, Amos J. Storkey, Michael F. P. O'Boyle:
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs. 24-34 - Ramyad Hadidi, Jiashen Cao, Yilun Xie, Bahar Asgari, Tushar Krishna, Hyesoon Kim:
Characterizing the Deployment of Deep Neural Networks on Commercial Edge Devices. 35-48 - Nima Elyasi, Changho Choi, Anand Sivasubramaniam, Jingpei Yang, Vijay Balakrishnan:
Trimming the Tail for Deterministic Read Performance in SSDs. 49-58 - Anirudh Mohan Kaushik, Ashwin M. Aji, Muhammad Amber Hassaan, Noel Chalmers, Noah Wolfe, Scott Moe, Sooraj Puthoor, Bradford M. Beckmann:
Optimizing Hyperplane Sweep Operations Using Asynchronous Multi-grain GPU Tasks. 59-69 - Sarabjeet Singh, Manu Awasthi:
Efficacy of Statistical Sampling on Contemporary Workloads: The Case of SPEC CPU2017. 70-80 - Tuan Ta, Xianwei Zhang, Anthony Gutierrez, Bradford M. Beckmann:
Autonomous Data-Race-Free GPU Testing. 81-92 - Youngdong Do, Hyungmo Kim, Pyeongseok Oh, Daeyoung Park, Jaejin Lee:
SNU-NPB 2019: Parallelizing and Optimizing NPB in OpenCL and CUDA for Modern GPUs. 93-105 - Lev Mukhanov, Konstantinos Tovletoglou, Hans Vandierendonck, Dimitrios S. Nikolopoulos, Georgios Karakonstantis:
Workload-Aware DRAM Error Prediction using Machine Learning. 106-118 - Athanasios Chatzidimitriou, George Papadimitriou, Christos Gavanas, George Katsoridas, Dimitris Gizopoulos:
Multi-Bit Upsets Vulnerability Analysis of Modern Microprocessors. 119-130 - Ali Hadi Zadeh, Zissis Poulos, Andreas Moshovos:
Deep Learning Language Modeling Workloads: Where Time Goes on Graphics Processors. 131-142 - Alexander Hankin, Tomer Shapira, Karthik Sangaiah, Michael Lui, Mark Hempstead:
Evaluation of Non-Volatile Memory Based Last Level Cache Given Modern Use Case Behavior. 143-154 - Tyler Sorensen, Sreepathi Pai, Alastair F. Donaldson:
One Size Doesn't Fit All: Quantifying Performance Portability of Graph Applications on GPUs. 155-166 - Yishen Chen, Ajay Brahmakshatriya, Charith Mendis, Alex Renda, Eric Atkinson, Ondrej Sýkora, Saman P. Amarasinghe, Michael Carbin:
BHive: A Benchmark Suite and Measurement Framework for Validating x86-64 Basic Block Performance Models. 167-177 - Dipti Shankar, Xiaoyi Lu, Dhabaleswar K. D. K. Panda:
SimdHT-Bench: Characterizing SIMD-Aware Hash Table Designs on Emerging CPU Architectures. 178-188 - Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia:
Characterizing Deep Learning Training Workloads on Alibaba-PAI. 189-202 - Marzieh Lenjani, Patricia Gonzalez-Guerrero, Elaheh Sadredini, M. Arif Imtiazur Rahman, Mircea R. Stan:
An Overflow-free Quantized Memory Hierarchy in General-purpose Processors. 203-215 - Sungjoon Koh, Junhyeok Jang, Changrim Lee, Miryeong Kwon, Jie Zhang, Myoungsoo Jung:
Faster than Flash: An In-Depth Study of System Challenges for Emerging Ultra-Low Latency SSDs. 216-227 - Chit-Kwan Lin, Stephen J. Tarsa:
Branch Prediction Is Not A Solved Problem: Measurements, Opportunities, and Future Directions. 228-238 - Fan Yao, Kathy Ngyugen, Sai Santosh Dayapule, Jingxin Wu, Bingqian Lu, Suresh Subramaniam, Guru Venkataramani:
HolDCSim: A Holistic Simulator for Data Centers. 239-242 - Johnathan Alsop, Xianwei Zhang, Tsung Tai Yeh, Bradford M. Beckmann, Matthew D. Sinclair, Srikant Bharadwaj, Alexandru Dutu, Anthony Gutierrez, Onur Kayiran, Michael LeBeane, Brandon Potter, Sooraj Puthoor:
Optimizing GPU Cache Policies for MI Workloads. 243-248 - Xiao Liu, Bhaskar Jupudi, Pankaj Mehra, Jishen Zhao:
Persistent Memory Workload Characterization: A Hardware Perspective. 249-252 - Pengfei Zou, Ang Li, Kevin J. Barker, Rong Ge:
Fingerprinting Anomalous Computation with RNN for GPU-accelerated HPC Machines. 253-256 - Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang:
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators. 257-262 - Zamshed I. Chowdhury, S. Karen Khatamifard, Zhaoyong Zheng, Tali Moreshet, R. Iris Bahar, Ulya R. Karpuzcu:
Barrier Synchronization vs. Voltage Noise: A Quantitative Analysis. 263-267 - Ruidong Gu, Paul Beata, Michela Becchi:
Characterizing the Performance/Accuracy Tradeoff of High-Precision Applications via Auto-tuning. 268-272
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