HiPC 2020
PROGRAM DETAILS
DAY1
Wednesday, 16th December
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. Click here 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).
16th December 2020, TIME: 9am to 10am IST
Kathy Yelick
University of California at Berkeley and Lawrence Berkeley National Laboratory
Computing and Data Challenges in Climate Change
Paper Presentations
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 (11:20am IST)
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
DAY2
Thursday,17th December
16th December 2020, TIME: 9am to 10am IST
Animashree Anandkumar
Bren Professor of Computing at California Institute of Technology and Director of Machine Learning Research at NVIDIA
TITLE OF THE TALK: ABSTRACT
TBA
SPEAKER BIO
Anima Anandkumar is a Bren Professor at Caltech and Director of ML Research at NVIDIA. She was previously a Principal Scientist at Amazon Web Services. She has received several honors such as Alfred. P. Sloan Fellowship, NSF Career Award, Young investigator awards from DoD, and Faculty Fellowships from Microsoft, Google, Facebook, and Adobe. She is part of the World Economic Forum’s Expert Network. She is passionate about designing principled AI algorithms and applying them in interdisciplinary applications. Her research focus is on unsupervised AI, optimization, and tensor methods.
Paper Presentations
SESSION 2: Scalable Data Science (10:10 AM IST)
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)
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
DAY3
Friday,18th December
17th December 2020, TIME: 9am to 10am IST
Fabrizio Petrini
Intel Corporation, Parallel Computing Lab
TITLE OF THE TALK
TBA
SPEAKER BIO
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Paper Presentations
SESSION 4 : Runtime Systems (10:10 AM IST)
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 (11:20 AM IST)
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