Accepted Papers

HiPC 2019

HPC Tracks

Algorithms

A Deterministic Multi-Layered Partitioning Tool for Wire-length Reduction of Monolithic 3D-IC”,  Soumendu Ghorui, Sabyasachee Banerjee and Subhashis Majumder  

Mapping Arbitrarily Sparse Two-body Interactions on One-dimensional Quantum Circuits”, Arif Khan, Mahantesh Halappanavar, Tobias Hagge, Karol Kowalski, Alex Pothen and Sriram Krishnamoorthy  

HyDetect: A Hybrid CPU-GPU Algorithm for Community Detection”,  Anwesha Bhowmik and Sathish Vadhiyar 

Efficient Parallel Multi-bunch Beam-Beam Simulation in Particle Colliders”,    Ioannis Sakiotis, Kamesh Arumugam, Desh Ranjan, Balsa Terzic and Mohammad Zubair   

 

Applications

On Linear Learning with Manycore Processors”,  Eliza Wszola, Celestine Mendler-Dünner, Martin Jaggi and Markus Püschel  

Hierarchical Filter and Refinement System over Large Polygonal Datasets on CPU-GPU” , Yiming Liu, Jie Yang and Satish Puri   

Geostatistical Modeling and Prediction using Mixed Precision Tile Cholesky Factorization” , Sameh Abdulah, Hatem Ltaief, Ying Sun, Marc Genton and David Keyes

SPEC2: SPECtral SParsE CNN Accelerator on FPGAs”, Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang and Viktor Prasanna, Elnaz Tavakoli Yazdi, Ankur Limaye, Ali Akoglu, Tosiron Adegbija and Adam Buntzman    

Architecture-Centric Bottleneck Analysis for Deep Neural Network  Applications”, Jihyun Ryoo, Mengran Fan, Xulong Tang, Huaipan Jiang, Meena Arunachalam, Sharada Naveen and Mahmut Kandemir  

Distributed Relational Algebra at Scale”, Sidharth Kumar and Thomas Gilray    

Efficient Sparse Neural Networks using Regularized Multi Block Sparsity Pattern on a GPU”, Dharma Teja Vooturi and Kishore Kothapalli      

 

Architectures

Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems”, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang and Kailash Gopalakrishnan        

IsoKV: An Isolation Scheme for Key-value Stores by Exploiting Internal Parallelism in SSD”, Heerak Lim, Hwajung Kim, Kihyeon Myung, Heon Young Yeom and Yongseok Son  

SCOR-KV: SIMD-Aware Client-Centric and Optimistic RDMA-based Key-Value Store for Emerging CPU Architectures”, Dipti Shankar, Xiaoyi Lu and Dhabaleswar K. Panda      

High-Performance Adaptive MPI Derived Datatype Communication for Modern Multi-GPU Systems”, Ching-Hsiang Chu, Jahanzeb Maqbool Hashmi, Kawthar Shafie Khorassani, Hari Subramoni and Dhabaleswar Panda      

Online Management of Hybrid DRAM-NVMM Memory for HPC”, Reza Salkhordeh and André Brinkmann 

MLBS: Transparent Data Caching in Hierarchical Storage for Out-of-Core HPC Applications”, Tariq Alturkestani, Thierry Tonellot, Hatem Ltaief, Rached Abdelkhalak, Vincent Etienne and David Keyes  

Evaluating the Impact of Energy Efficient Networks on HPC Workloads”, Giorgis Georgakoudis, Nikhil Jain, Takatsugu Ono, Koji Inoue, Shinobu Miwa and Abhinav Bhatele  

 

Systems Software

A Linux Kernel Scheduler Extension for Multi-Core Systems”, Aleix Roca, Samuel Rodriguez, Albert Segura, Vicenç Beltran and Kevin Marquet        

Reducing False Node Failure Predictions in HPC”, Alvaro Frank, Dai Yang, Andre Brinkmann, Martin Schulz and Tim Süss   

uMMAP-IO: User-level Memory-mapped I/O for HPC”, Sergio Rivas-Gomez, Alessandro Fanfarillo, Sebastien Valat, Christophe Laferriere, Philippe Couvee, Sai Narasimhamurthy and Stefano Markidis

Worksharing Tasks: an Efficient Way to Explot Irregular and Fine-Grained Loop Parallelism”, Marcos Maronas, Kevin Sala, Sergi Mateo, Vicenç Beltran and Eduard Ayguade        

Designing a Profiling and Visualization Tool for Scalable and In-Depth Analysis of High-Performance GPU Clusters”, Pouya Kousha, Bharath Ramesh, Kaushik Kandadi Suresh, Ching-Hsiang Chu, Arpan Jain, Nick Sarkauskas, Hari Subramoni and Dhabaleswar Panda

Tuning Object-centric Data Management Systems for Large Scale Scientific Applications “, Houjun Tang, Suren Byna, Stephen Bailey, Zarija Lukic, Jialin Liu, Quincey Koziol and Bin Dong      

Empirical analysis of hardware-assisted GPU virtualization”, Anshuj Garg, Purushottam Kulkarni, Uday Kurkure, Hari Sivaraman and Lan Vu   

Ground-Truth Prediction to Accelerate Soft-ErrorImpact Analysis for Iterative Methods“, Burcu O. Mutlu, Gokcen Kestor, Adrian Cristal, Osman Unsal and Sriram Krishnamoorthy 

 

Data Science Tracks

Data Systems

DeepSparse: A Task-parallel Framework for Sparse Solvers on Deep Memory Architectures”, Md Afibuzzaman, Fazlay Rabbi, M Yusuf Ozkaya, Hasan Metin Aktulga and Umit Catalyurek

Analysis in the Data Path of an Object-centric Data Management System”, Richard Warren, Jerome Soumagne, Jingqing Mu, Houjun Tang, Suren Byna, Bin Dong and Quincey Koziol         

k-NN Sampling for Visualization of Dynamic data using LION-tSNE”, Dharamsotu Bheekya, K Swarupa Rani, Salman Abdul Moiz and C. Raghavendra Rao  

Exploring Metadata Search Essentials for Scientific Data Management”, Wei Zhang, Suren Byna, Chenxu Niu and Yong Chen 

User-Level Scheduled Communications for MPI”,  Derek Schafer, Sheikh Ghafoor, Daniel J. Holmes, Martin Ruefenacht and Anthony Skjellum     

 

Data Algorithms

Optimizing Breadth-First Search at Scale Using Hardware Accelerated Collectives”, Khaled Ibrahim    

Acceleration of Sparse Vector Autoregressive Modeling using GPUs”, Shreenivas Bharadwaj Venktaramanan, Yogish Sabhaarwal and Rahul Garg  

Shared-Memory Parallel Maximal Biclique Enumeration”, Apurba Das and Srikanta Tirthapura

Replaceability based Web Service Selection Approach”, Lalit Purohit and Dr Sandeep Kumar 

Accelerating Data Loading in Deep Neural Network Training”, Chih-Chieh Yang and Guojing Cong      

Efficient Memory Pool Allocation Algorithm for CNN Inference”,  Arun Abraham, Manas Sahni and Akshay Parashar  

Fast and Accurate Learning of Knowledge Graph Embeddings at Scale”, Udit Gupta and Sathish Vadhiyar  

 

 

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