*********************************************************************** CALL FOR PARTICIPATION IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2020 https://hipc.org/ ***********************************************************************

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