[hpc-announce] IEEE HiPC 2020 Call For Participation

[sanmukh at hipc.org]

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CALL FOR PARTICIPATION
IEEE International Conference on High Performance Computing, Data, and
Analytics, HiPC  2020
https://hipc.org/
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HiPC 2020 is the 27th edition of the IEEE International Conference on
High Performance Computing, Data, and Analytics. The conference focus
is not only HPC but also includes Data Science.  Due to the COVID-19
pandemic, this year the conference will be held virtually on December
16, 17, and 18. Each day of the three day event will open with a
keynote talk, followed by two one-hour live remote sessions to present
the technical program of thirty-three peer reviewed papers. All papers
accepted for the conference will be published as part of the
proceedings that will be available before, during, and after the week
of the scheduled conference. The online publication will include both
papers and presentations (slides) for each paper. Access to the online
publication is part of the free registration to attend the virtual
live sessions. See here (https://hipc.org/register2020/) to register.
Below is the planned program schedule for the conference. Return
regularly for updates and details on how to attend. All times below
are India Standard Time (IST).


Wednesday, December 16th


Keynote Talk (9:00-10:00 AM IST)


	Kathy Yelick
University of California at Berkeley and
Lawrence Berkeley National Laboratory


Computing and Data Challenges in Climate Change
	

Best Papers Session (10:10 AM IST – start time)


SimGQ: Simultaneously Evaluating Iterative Graph Queries
Chengshuo Xu, Abbas Mazloumi, Xiaolin Jiang and Rajiv Gupta

WarpCore: A Library for fast Hash Tables on GPUs
Daniel Jünger, Robin Kobus, André Müller, Kai Xu, Weiguo Liu,
Christian Hundt and Bertil Schmidt


Session 1: Applications (11:20 AM IST – start time)


Towards High Performance, Portability, and Productivity: Lightweight
Augmented Neural Networks for Performance Prediction
Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan and Viktor K. Prasanna.


Performance Optimization and Scalability Analysis of the MGB Hydrological Model
Henrique R. A. Freitas, Celso Luiz Mendes and Aleksandar Ilic


Exploring Task Parallelism for the Multilevel Fast Multipole Algorithm
Michael Lingg, H. Metin Aktulga, Balasubramaniam Shanker, Stephen
Hughey and Doga Dikbayir


SparsePipe: Parallel Deep Learning for 3D Point Clouds
Keke Zhai, Pan He, Tania Banerjee, Anand Rangarajan and Sanjay Ranka


HyPR: Hybrid Page Ranking on Evolving Graphs
Hemant Kumar Giri, Mridul Haque and Dip Sankar Banerjee


Distributing Sparse Matrix/Graph Applications in Heterogeneous
Clusters -- an Experimental Study
Charilaos Tzovas, Maria Predari and Henning Meyerhenke


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Thursday, December 17th


Keynote Talk (9:00-10:00 AM IST)


	

Animashree Anandkumar
California Institute of Technology and
Machine Learning Research, NVIDIA

Role of HPC in next-generation AI


	

Session 2: Scalable Data Science (10:10 AM IST – start time)


Processor Pipelining Method for Efficient Deep Neural Network
Inference on Embedded Devices
Akshay Parashar, Arun Abraham, Deepak Chaudhary and Vikram Nelvoy Rajendiran


Avoiding Communication in Logistic Regression
Aditya Devarakonda and James Demmel


A Parallel and Scalable Framework for Insider Threat Detection
Abdoulaye Diop, Nahid Emad and Thierry Winter


Blink: Towards Efficient RDMA-based Communication Coroutines for
Parallel Python Applications
Aamir Shafi, Jahanzeb Maqbool Hashmi, Hari Subramoni and Dhabaleswar K. Panda


Content-defined Container Delivery
Yuta Nakamura, Tanu Malik and Raza Ahmad


Model Checking as a Service using Dynamic Resource Scaling
Surya Teja, Yuvraj Singh, Adhish Singla, Suresh Purini and Venkatesh Choppella


Session 3: Algorithms (11:20 AM IST – start time)


Parallel Hierarchical Clustering using Rank-Two Nonnegative Matrix Factorization
Lawton Manning, Grey Ballard, Ramakrishnan Kannan and Haesun Park


Pipelined Preconditioned Conjugate Gradient Methods for Distributed
Memory Systems
Manasi Tiwari and Sathish Vadhiyar


Fair Allocation of Asymmetric Operations in Storage Systems
Thomas Keller and Peter Varman


A GPU Algorithm for Earliest Arrival Time Problem in Public Transport Networks
Chirayu Anant Haryan, G. Ramakrishna, Rupesh Nasre and Allam Dinesh Reddy


2D Static Resource Allocation Strategies for Load Balancing in
Compressed Linear Algebra under Communication Constraints
Olivier Beaumont, Lionel Eyraud-Dubois and Mathieu Verite


Algorithms for Preemptive Co-scheduling of Kernels on GPUs
Lionel Eyraud-Dubois and Cristiana Bentes


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Friday, December 18th


Keynote Talk (9:00-10:00 AM IST)


	

Fabrizio Petrini
Parallel Computing Lab
Intel Corporation


Breaking the Scalability Wall
	

Session 4: Runtime Systems (10:10 AM IST – start time)


Understanding HPC Application I/O Behavior Using System Level Statistics
Arnab K. Paul, Olaf Faaland, Adam Moody, Elsa Gonsiorowski, Kathryn
Mohror and Ali R. Butt


AMCilk: A Framework for Multiprogrammed Parallel Workloads
Zhe Wang, Chen Xu, Kunal Agrawal and Jing Li


Extending SLURM for Dynamic Resource-Aware Adaptive Batch Scheduling
Mohak Chadha, Jophin John and Michael Gerndt


On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance
Joshua Suetterlein, Joseph Manzano, Andres Marquez and Gunag Gao


Exposing data locality in HPC-based systems by using the HDFS backend
Jose Rivadeneira, Felix Garcia-Carballeira, Jesus Carretero and Javier
Garcia-Blas


PufferFish: NUMA-Aware Work-stealing Library using Elastic Tasks
Vivek Kumar


Design and Study of Elastic Recovery in HPC Applications
Kai Keller, Konstantinos Parasyris and Leonardo Bautista


Session 5: System Software and Architecture (11:30 AM IST – start time)


Accelerating Force-directed Graph Layout with Processing-in-Memory Architecture
Ruihao Li, Shuang Song, Qinzhe Wu and Lizy K. John


Nonblocking Persistent Software Transactional Memory
Alan Beadle, Wentao Cai, Haosen Wen and Michael Scott


GPU-FPtuner: Mixed-precision Auto-tuning for Floating-point Applications on GPU
Ruidong Gu and Michela Becchi


Batched Small Tensor-Matrix Multiplications On GPUs
Keke Zhai, Tania Banerjee, Adeesha Wijayasiri and Sanjay Ranka


Temporal Based Intelligent LRU Cache Construction
Pavan Nittur, Anuradha Kanukotla and Narendra Mutyala


Boosting LSTM Performance Through Dynamic Precision Selection
Franyell Silfa, Jose Maria Arnau and Antonio González