dblp: ISPASS 2019 (original) (raw)

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ISPASS 2019: Madison, WI, USA

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  • Paper Session I: Best Paper Nominees
  • Paper Session II: Analyis Tools
  • Paper Session III: System Characterization
  • Poster Session
  • Paper Session IV: Workload Characterization
  • Paper Session V: Data Centers and Cloud Computing
  • Paper Session VI: Performance Modeling and Prediction

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  IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2019, Madison, WI, USA, March 24-26, 2019. IEEE 2019, ISBN 978-1-7281-0746-2

Paper Session I: Best Paper Nominees

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    Zacharias Hadjilambrou, Shidhartha Das, Paul N. Whatmough, David M. Bull, Yiannakis Sazeides:
    GeST: An Automatic Framework For Generating CPU Stress-Tests. 1-10
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    Hossein Golestani, Scott A. Mahlke, Satish Narayanasamy:
    Characterization of Unnecessary Computations in Web Applications. 11-21
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    Runchao Han, Nikos Foutris, Christos Kotselidis:
    Demystifying Crypto-Mining: Analysis and Optimizations of Memory-Hard PoW Algorithms. 22-33
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    Matthew Halpern, Behzad Boroujerdian, Todd W. Mummert, Evelyn Duesterwald, Vijay Janapa Reddi:
    One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-Off in Machine Learning Cloud Service APIs via Tolerance Tiers. 34-47

Paper Session II: Analyis Tools

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    Karl Taht, James Greensky, Rajeev Balasubramonian:
    The POP Detector: A Lightweight Online Program Phase Detection Framework. 48-57
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    Almutaz Adileh, Cecilia González-Alvarez, Juan Miguel De Haro Ruiz, Lieven Eeckhout:
    Racing to Hardware-Validated Simulation. 58-67
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    Kuba Kaszyk, Harry Wagstaff, Tom Spink, Björn Franke, Michael F. P. O'Boyle, Bruno Bodin, Henrik Uhrenholt:
    Full-System Simulation of Mobile CPU/GPU Platforms. 68-78
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    Md Aamir Raihan, Negar Goli, Tor M. Aamodt:
    Modeling Deep Learning Accelerator Enabled GPUs. 79-92
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    Shoaib Akram, Jennifer B. Sartor, Kathryn S. McKinley, Lieven Eeckhout:
    Emulating and Evaluating Hybrid Memory for Managed Languages on NUMA Hardware. 93-105

Paper Session III: System Characterization

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    Yufeng Zhou, Xiaowan Dong, Alan L. Cox, Sandhya Dwarkadas:
    On the Impact of Instruction Address Translation Overhead. 106-116
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    Guru Prasad Srinivasa, Scott Haseley, Geoffrey Challen, Mark Hempstead:
    Quantifying Process Variations and Its Impacts on Smartphones. 117-126
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    Athanasios Chatzidimitriou, George Papadimitriou, Dimitris Gizopoulos, Shrikanth Ganapathy, John Kalamatianos:
    Assessing the Effects of Low Voltage in Branch Prediction Units. 127-136

Poster Session

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    Aajna Karki, Chethan Palangotu Keshava, Spoorthi Mysore Shivakumar, Joshua Skow, Goutam Madhukeshwar Hegde, Hyeran Jeon:
    Tango: A Deep Neural Network Benchmark Suite for Various Accelerators. 137-138
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    Dilip P. Vasudevan, George Michelogiannakis, David Donofrio, John Shalf:
    PARADISE - Post-Moore Architecture and Accelerator Design Space Exploration Using Device Level Simulation and Experiments. 139-140
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    Mahmoud Khairy, Akshay Jain, Tor M. Aamodt, Timothy G. Rogers:
    A Detailed Model for Contemporary GPU Memory Systems. 141-142
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    Suk-Joo Chae, Tae-Sun Chung:
    DSMM: A Dynamic Setting for Memory Management in Apache Spark. 143-144
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    Jiancong Ge, Ming Ling:
    Fast Modeling of the L2 Cache Reuse Distance Histograms from Software Traces. 145-146
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    Bradley Wang, Ayaz Akram, Jason Lowe-Power:
    FlexCPU: A Configurable Out-of-Order CPU Abstraction. 147-148
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    Qi Yu, Bruce R. Childers, Libo Huang, Cheng Qian, Zhiying Wang:
    Hierarchical Page Eviction Policy for Unified Memory in GPUs. 149-150
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    Jonathan S. Lew, Deval A. Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth Sandhupatla, Christopher Ng, Negar Goli, Matthew D. Sinclair, Timothy G. Rogers, Tor M. Aamodt:
    Analyzing Machine Learning Workloads Using a Detailed GPU Simulator. 151-152

Paper Session IV: Workload Characterization

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    Joo Hwan Lee, Hyesoon Kim:
    Empirical Investigation of Stale Value Tolerance on Parallel RNN Training. 153-164
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    Milos Nikolic, Mostafa Mahmoud, Andreas Moshovos, Yiren Zhao, Robert Mullins:
    Characterizing Sources of Ineffectual Computations in Deep Learning Networks. 165-176
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    Yu Emma Wang, Yuhao Zhu, Glenn G. Ko, Brandon Reagen, Gu-Yeon Wei, David Brooks:
    Demystifying Bayesian Inference Workloads. 177-189
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    Enrico Armenio Deiana, Simone Campanoni:
    Workload Characterization of Nondeterministic Programs Parallelized by STATS. 190-201
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    Siying Feng, Subhankar Pal, Yichen Yang, Ronald G. Dreslinski:
    Parallelism Analysis of Prominent Desktop Applications: An 18- Year Perspective. 202-211

Paper Session V: Data Centers and Cloud Computing

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    Yanqi Zhang, Yu Gan, Christina Delimitrou:
    µqSim: Enabling Accurate and Scalable Simulation for Interactive Microservices. 212-222
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    Paul Reeser, Guilhem Tesseyre, Marcus Callaway:
    Distributed Software Defined Networking Controller Failure Mode and Availability Analysis. 223-232
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    Kewen Wang, Mohammad Maifi Hasan Khan, Nhan Nguyen, Swapna S. Gokhale:
    A Model Driven Approach Towards Improving the Performance of Apache Spark Applications. 233-242
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    Sahel Sharify, Alan W. Lu, Jin Chen, Arnamoy Bhattacharyya, Ali B. Hashemi, Nick Koudas, Cristiana Amza:
    An Improved Dynamic Vertical Partitioning Technique for Semi-Structured Data. 243-256

Paper Session VI: Performance Modeling and Prediction

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    Sander De Pestel, Sam Van den Steen, Shoaib Akram, Lieven Eeckhout:
    RPPM: Rapid Performance Prediction of Multithreaded Workloads on Multicore Processors. 257-267
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    Masab Ahmad, Halit Dogan, Christopher J. Michael, Omer Khan:
    HeteroMap: A Runtime Performance Predictor for Efficient Processing of Graph Analytics on Heterogeneous Multi-Accelerators. 268-281
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    Zhongyuan Zhao, Hyoukjun Kwon, Sachit Kuhar, Weiguang Sheng, Zhigang Mao, Tushar Krishna:
    mRNA: Enabling Efficient Mapping Space Exploration for a Reconfiguration Neural Accelerator. 282-292
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    Sangkug Lym, Donghyuk Lee, Mike O'Connor, Niladrish Chatterjee, Mattan Erez:
    DeLTA: GPU Performance Model for Deep Learning Applications with In-Depth Memory System Traffic Analysis. 293-303
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    Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Stephen W. Keckler, Joel S. Emer:
    Timeloop: A Systematic Approach to DNN Accelerator Evaluation. 304-315

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