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ORCIDIPDPS 2022: Lyon, France - Workshops
- IEEE International Parallel and Distributed Processing Symposium, IPDPS Workshops 2022, Lyon, France, May 30 - June 3, 2022. IEEE 2022, ISBN 978-1-6654-9747-3
- Anne Benoit, Laurent Lefèvre:
Message from the 2022 General Co-Chairs. xxviii-xxix - Robin Abrahamse, Ákos Hadnagy, Zaid Al-Ars:
Memory-Disaggregated In-Memory Object Store Framework for Big Data Applications. 1-7 - Pascal Costanza, Ibrahim Hur, Timothy G. Mattson:
Towards a GraphBLAS Implementation for Go. 1-4 - Junqi Yin
, Feiyi Wang, Mallikarjun Shankar:
Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications. 1-10 - Natsuki Hamada, Kazuhiro Saito, Hideyuki Kawashima:
Practical Effectiveness of Quantum Annealing for Shift Scheduling Problem. 1-4 - Stephanie Brink:
AI for Datacenter Optimization (ADOPT'22). 1 - Laurent White:
HCW 2022 Keynote Speaker: Heterogeneous Computing for Scientific Machine Learning. 5 - Shashank Adavally, Alex Weaver, Pranathi Vasireddy, Krishna Kavi, Gayatri Mehta, Nagendra Gulur:
HETEROGENEOUS ARCHITECTURE FOR SPARSE DATA PROCESSING. 6-15 - Enrico Russo, Maurizio Palesi, Davide Patti, Habiba Lahdhiri, Salvatore Monteleone, Giuseppe Ascia, Vincenzo Catania:
Combined Application of Approximate Computing Techniques in DNN Hardware Accelerators. 16-23 - Chen-Chun Chen, Kawthar Shafie Khorassani, Quentin G. Anthony, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Highly Efficient Alltoall and Alltoallv Communication Algorithms for GPU Systems. 24-33 - Ravi Reddy Manumachu, Alexey L. Lastovetsky:
On Energy Nonproportionality of CPUs and GPUs. 34-44 - Johannes Moe, Konstantin Pogorelov, Daniel Thilo Schroeder, Johannes Langguth:
Implementating Spatio-Temporal Graph Convolutional Networks on Graphcore IPUs. 45-54 - Giorgos Vasiliadis, Rafail Tsirbas, Sotiris Ioannidis:
The Best of Many Worlds: Scheduling Machine Learning Inference on CPU-GPU Integrated Architectures. 55-64 - Jürgen Becker, Lana Josipovic, Viktor K. Prasanna, Marco D. Santambrogio, Ramachandran Vaidyanathan:
29th Reconfigurable Architectures Workshop (RAW 2022). 65-66 - Gustavo Alonso:
RAW 2022 Keynote Speaker 1: Using FPGAs in datacenters and the cloud. 67 - Gustavo Alonso:
RAW 2022 Keynote Speaker 1: Using FPGAs in datacenters and the cloud. 68 - Daniele Paletti, Francesco Peverelli, Davide Conficconi:
Online Learning RTL Synthesis for Automated Design Space Exploration. 69-76 - Dana Diaconu, Lucian Petrica, Michaela Blott, Miriam Leeser:
Machine Learning Aided Hardware Resource Estimation for FPGA DNN Implementations. 77-83 - Lester Kalms, Tim Haering, Diana Goehringer:
DECISION: Distributing OpenVX Applications on CPUs, GPUs and FPGAs using OpenCL. 84-91 - Jonas Ney, Bilal Hammoud, Norbert Wehn:
A Hybrid Approach combining ANN-based and Conventional Demapping in Communication for Efficient FPGA-Implementation. 92-95 - Pascal Jungblut, Dieter Kranzlmüller:
Optimal Schedules for High-Level Programming Environments on FPGAs with Constraint Programming. 96-99 - Seung-Hun Chung, Tarek S. Abdelrahman:
Optimization of Compiler-Generated OpenCL CNN Kernels and Runtime for FPGAs. 100-103 - Raffaele Berzoini, Eleonora D'Arnese, Davide Conficconi:
On How to Push Efficient Medical Semantic Segmentation to the Edge: the SENECA approach. 104-111 - Lukas Weber, Johannes Wirth, Lukas Sommer, Andreas Koch:
Exploiting High-Bandwidth Memory for FPGA-Acceleration of Inference on Sum-Product Networks. 112-119 - Lennart Clausing, Marco Platzner:
ReconOS64: A Hardware Operating System for Modern Platform FPGAs with 64-Bit Support. 120-127 - Tze Hon Tan, Chia Yee Ooi, Muhammad N. Marsono:
An FPGA-based IP Core Subscription-Oriented Fog Computing Platform. 128-131 - Mingyuan Yang, Yemeng Zhang, Bohan Yang, Hanning Wang, Shouyi Yin, Shaojun Wei, Leibo Liu:
A SHA-512 Hardware Implementation Based on Block RAM Storage Structure. 132-135 - Beatrice Branchini, Sofia Breschi, Alberto Zeni, Marco D. Santambrogio:
Fast Genome Analysis Leveraging Exact String Matching. 136-139 - Christina Boucher:
Building scalable indexes that can be efficiently queried. 142 - Yatish Turakhia:
HiCOMB 2022 Invited Speaker: Pandemic-scale Phylogenetics. 143 - Yiqing Yan, Nimisha Chaturvedi, Raja Appuswamy:
Optimizing the Accuracy of Randomized Embedding for Sequence Alignment. 144-151 - Mario João Jr., Alexandre da Costa Sena, Vinod E. F. Rebello:
On Using Consistency Consistently in Multiple Sequence Alignments. 152-161 - Joël Lindegger, Damla Senol Cali, Mohammed Alser, Juan Gómez-Luna, Onur Mutlu:
Algorithmic Improvement and GPU Acceleration of the GenASM Algorithm. 162 - Safaa Diab, Amir Nassereldine, Mohammed Alser, Juan Gómez-Luna, Onur Mutlu, Izzat El Hajj:
High-throughput Pairwise Alignment with the Wavefront Algorithm using Processing-in-Memory. 163 - Haris Smajlovic, Ariya Shajii, Bonnie Berger, Hyunghoon Cho, Ibrahim Numanagic:
Sequre: a high-performance framework for rapid development of secure bioinformatics pipelines. 164-165 - Alvin Chon, Pawel Górecki, Oliver Eulenstein, Xiaoqiu Huang, Ali Jannesari:
Scalable and Extensible Robinson-Foulds for Comparative Phylogenetics. 166-175 - Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul:
Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data. 176-185 - Anoop Kumar, Vibha Balaji, M. A. Chandrashekar, Ambedkar Dukkipati, Sathish Vadhiyar:
Graph Convolutional Neural Networks for Alzheimer's Classification with Transfer Learning and HPC Methods. 186-195 - Reinout Corts, Niek Sterenborg, Nikolaos Alachiotis:
Accelerated LD-based selective sweep detection using GPUs and FPGAs. 196-205 - Mu Gao, Mark Coletti, Russell B. Davidson, Ryan Prout, Subil Abraham, Benjamín Hernández, Ada Sedova:
Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer. 206-215 - Pelin Icer Baykal, Niko Beerenwinkel, Serghei Mangul:
Reproducibility of Bioinformatics Tools. 216 - Varuni Sarwal, Serghei Mangul, David Koslicki:
TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles. 217 - Tim Mattson:
GrAPL 2022 Keynote Speaker: GraphBLAS Beyond Simple Graphs. 220 - Ilya V. Afanasyev, Kazuhiko Komatsu, Dmitry I. Lichmanov, Vadim V. Voevodin, Hiroaki Kobayashi:
High-Performance GraphBLAS Backend Prototype for NEC SX-Aurora TSUBASA. 221-229 - Aristeidis Mastoras, Sotiris Anagnostidis, Albert-Jan Nicholas Yzelman:
Nonblocking execution in GraphBLAS. 230-233 - Benjamin Brock, Scott McMillan, Aydin Buluç, Timothy G. Mattson, José E. Moreira:
GraphBLAS: C++ Iterators for Sparse Matrices. 238-246 - Jeremy Kepner, Michael Jones, Daniel Andersen, Aydin Buluç, Chansup Byun, kc claffy, Timothy Davis, William Arcand, Jonathan Bernays, David Bestor, William Bergeron, Vijay Gadepally, Daniel Grant, Micheal Houle, Matthew Hubbell, Hayden Jananthan, Anna Klein, Chad R. Meiners, Lauren Milechin, Andrew Morris, Julie Mullen, Sandeep Pisharody, Andrew Prout, Albert Reuther, Antonio Rosa, Siddharth Samsi, Doug Stetson, Charles Yee, Peter Michaleas:
Temporal Correlation of Internet Observatories and Outposts. 247-254 - Eugenio Angriman, Fabian Brandt-Tumescheit, Leon Franke, Alexander van der Grinten, Henning Meyerhenke:
Interactive Visualization of Protein RINs using NetworKit in the Cloud. 255-264 - Somesh Singh, Bora Uçar:
An Efficient Parallel Implementation of a Perfect Hashing Method for Hypergraphs. 265-274 - Xu T. Liu, Jesun Firoz, Assefaw H. Gebremedhin, Andrew Lumsdaine:
NWHy: A Framework for Hypergraph Analytics: Representations, Data structures, and Algorithms. 275-284 - Md Taufique Hussain, Guttu Sai Abhishek, Aydin Buluç, Ariful Azad:
Parallel Algorithms for Adding a Collection of Sparse Matrices. 285-294 - Le Chen, Quazi Ishtiaque Mahmud, Ali Jannesari:
Multi-View Learning for Parallelism Discovery of Sequential Programs. 295-303 - Jay A. Acosta, Tze Meng Low, Devangi N. Parikh:
Families of Butterfly Counting Algorithms for Bipartite Graphs. 304-313 - Muhammad Osama, Serban D. Porumbescu, John D. Owens:
Essentials of Parallel Graph Analytics. 314-317 - Rajendra K. Raj:
"Crosscutting Themes in Computer Science: Where Does PDC Education Fit?". 320 - Tia Newhall, Kevin C. Webb, Vasanta Chaganti, Andrew Danner:
Introducing Parallel Computing in a Second CS Course. 321-329 - Jérémy Fix, Stéphane Vialle, Rémi Hellequin, Claudine Mercier, Patrick P. Mercier, Jean-Baptiste Tavernier:
Feedback from a data center for education at CentraleSupélec engineering school. 330-337 - Joel Antonio Trejo-Sánchez, Francisco Javier Hernández-López, Miguel Ángel Uh Zapata, José Luis López-Martínez, Daniel Fajardo-Delgado, Julio Cesar Ramírez Pacheco:
Teaching High-Performance Computing in Developing Countries: A Case Study in Mexican Universities. 338-345 - Patrick Bell, Kae Suarez, Barbara Fossum, Dylan Chapp, Sanjukta Bhowmick, Michela Taufer:
A Research-Based Course Module to Study Non-determinism in High Performance Applications. 346-353 - Joel Fuentes, Daniel López, Sebastián González:
Teaching Heterogeneous Computing Using DPC++. 354-360 - H. Martin Bücker, Henri Casanova, Rafael Ferreira da Silva, Alice Lasserre, Derrick Luyen, Raymond Namyst, Johannes Schoder, Pierre-André Wacrenier, David P. Bunde:
Peachy Parallel Assignments (EduPar 2022). 361-368 - Lena Oden:
12th IEEE International Workshop on Accelerators and Hybrid Emerging Systems. 369-370 - Estela Suarez:
AsHES 2022 Keynote Speaker: The Modular Supercomputing Architecture (MSA). 371 - Alan Ayala, Stan Tomov, Miroslav Stoyanov, Azzam Haidar, Jack J. Dongarra:
Performance Analysis of Parallel FFT on Large Multi-GPU Systems. 372-381 - Tristan Laan, Ana Lucia Varbanescu:
Heterogeneous GPU and FPGA computing: a VexCL case-study. 382-390 - Alok Mishra, Smeet Chheda, Carlos Soto, Abid Muslim Malik, Meifeng Lin, Barbara M. Chapman:
COMPOFF: A Compiler Cost model using Machine Learning to predict the Cost of OpenMP Offloading. 391-400 - Raul Torres, Roger Ferrer, Xavier Teruel:
A Novel Set of Directives for Multi-device Programming with OpenMP. 401-410 - Thorsten Koch, Daniel Rehfeldt, Yuji Shinano:
APDCM 2022 Keynote Talk: Solving QUBOs on Digital and Quantum Computers. 413 - Daiki Okonogi, Satoru Jimbo, Kota Ando, Thiem Van Chu, Jaehoon Yu, Masato Motomura, Kazushi Kawamura:
APC-SCA: A Fully-Parallel Annealing Algorithm with Autonomous Pinning Effect Control. 414-420 - Ryota Yasudo, Koji Nakano, Yasuaki Ito, Yuya Kawamata, Ryota Katsuki, Shiro Ozaki, Takashi Yazane, Kenichiro Hamano:
Graph-theoretic Formulation of QUBO for Scalable Local Search on GPUs. 425-434 - Robert Basili, Wenyang Qian, Shuo Tang, Austin Castellino, Mary Eshaghian-Wilner, Ashfaq Khokhar, Glenn R. Luecke, James P. Vary:
Performance Evaluations of Noisy Approximate Quantum Fourier Arithmetic. 435-444 - Yoshiyuki Morie, Yasutaka Wada, Ryohei Kobayashi, Ryuichi Sakamoto:
Performance Evaluation of Data Transfer API for Rank Level Approximate Computing on HPC Systems. 445-448 - Shulei Xu, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Arm meets Cloud: A Case Study of MPI Library Performance on AWS Arm-based HPC Cloud with Elastic Fabric Adapter. 449-456 - Osamu Ishimura, Yoshihide Yoshimoto:
Aspect-Oriented Programming based building block platform to construct Domain-Specific Language for HPC application. 457-466 - Sam White, Laxmikant V. Kalé:
Optimizing Non-commutative Allreduce Over Virtualized, Migratable MPI Ranks. 467-475 - Alexandre Denis, Emmanuel Jeannot, Philippe Swartvagher:
Modeling Memory Contention between Communications and Computations in Distributed HPC Systems. 476-485 - Nooshin Nokhanji, Paola Flocchini, Nicola Santoro:
Fully Dynamic Line Maintenance by Hybrid Programmable Matter. 486-495 - Zheming Jin, Jeffrey S. Vetter:
Integer Sum Reduction with OpenMP on an AMD MI100 GPU. 496-499 - Koji Nakano, Victor Poupet:
Optimal Triangulation on the High Bandwidth Memory Model. 500-507 - Kinan Al-Attar, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Towards Java-based HPC using the MVAPICH2 Library: Early Experiences. 510-519 - Ioannis Vardas, Sascha Hunold, Jordy I. Ajanohoun, Jesper Larsson Träff:
mpisee: MPI Profiling for Communication and Communicator Structure. 520-529 - Simon Schwitanski, Felix Tomski, Joachim Protze, Christian Terboven, Matthias S. Müller:
An On-the-Fly Method to Exchange Vector Clocks in Distributed-Memory Programs. 530-540 - Tao Tao, David A. Plaisted:
Automatic Parallelization of Programs via Software Stream Rewriting. 541-551 - Charly Castes, Emmanuel Agullo, Olivier Aumage, Emmanuelle Saillard:
Decentralized in-order execution of a sequential task-based code for shared-memory architectures. 552-561 - Zheming Jin, Jeffrey S. Vetter:
Evaluating Unified Memory Performance in HIP. 562-568 - Jaemin Choi, David F. Richards, Laxmikant V. Kalé:
Improving Scalability with GPU-Aware Asynchronous Tasks. 569-578 - Shayan Manoochehri, Patrick Cristofaro, Dhrubajyoti Goswami:
A Customizable Lightweight STM for Irregular Algorithms on GPU. 579-587 - Tsung-Wei Huang, Yibo Lin:
Concurrent CPU-GPU Task Programming using Modern C++. 588-597 - Ang Li, Qiang Guan:
International Workshop on Quantum Classical Cooperative Computing (QCCC 2022). 598 - Nathan Wiebe:
QCCC 2022 Keynote Talk: Hybrid Quantum / Classical Algorithms for Machine Learning. 599 - Elisha Siddiqui Matekole, Yao-Lung L. Fang, Meifeng Lin:
Methods and Results for Quantum Optimal Pulse Control on Superconducting Qubit Systems. 600-606 - Avah Banerjee, Xin Liang, R. Tohid:
Locality-aware Qubit Routing for the Grid Architecture. 607-613 - Betis Baheri, Qiang Guan, Shuai Xu, Vipin Chaudhary:
SQCC: Smart Quantum Circuit Cutting. 614-615 - Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li:
Improving Variational Quantum Algorithms performance through Weighted Quantum Ensembles. 616-617 - Samuel Alexander Stein, Nathan Wiebe, James A. Ang, Ang Li:
Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite. 618-624 - Artur Podobas, Kentaro Sano, Jason Anderson:
The First International Workshop on Coarse-Grained Reconfigurable Architectures for High-Performance Computing (CGRA4HPC). 625-626 - Raghu Prabhakar:
(CGRA4HPC) 2022 Invited Speaker: Pushing the Boundaries of HPC with the Integration of AI. 627 - Elliott Delaye:
CGRA4HPC 2022 Invited Speaker: Mapping ML to the AMD/Xilinx AIE-ML architecture. 628 - Martin Snelgrove:
CGRA4HPC 2022 Invited Speaker: Dual-scale reconfigurable arrays for ML Inference. 629 - Ilan Tayari:
CGRA4HPC 2022 Invited Speaker: Practical, scalable, and easy-to-use CGRA for HPC. 630 - Takuya Kojima, Boma A. Adhi, Carlos Cortes, Yiyu Tan, Kentaro Sano:
An Architecture- Independent CGRA Compiler enabling OpenMP Applications. 631-638 - Boma A. Adhi, Carlos Cortes, Yiyu Tan, Takuya Kojima, Artur Podobas, Kentaro Sano:
Exploration Framework for Synthesizable CGRAs Targeting HPC: Initial Design and Evaluation. 639-646 - Markus Weinhardt:
An Analysis of Mapping Polybench Kernels to HPC CGRAs. 647-654 - Omar Ragheb, Tianyi Yu, Rami Beidas, Jason Helge Anderson:
Elastic Multi-Context CGRAs. 655-662 - Sho Ko, Alexander Rucker, Yaqi Zhang, Paul Mure, Kunle Olukotun:
Accelerating SLIDE: Exploiting Sparsity on Accelerator Architectures. 663-670 - Hoai Luan Pham, Thi Hong Tran, Vu Trung Duong Le, Yasuhiko Nakashima:
A Coarse Grained Reconfigurable Architecture for SHA-2 Acceleration. 671-678 - Kevin J. M. Martin:
Twenty Years of Automated Methods for Mapping Applications on CGRA. 679-686 - Lidia Kidane, Paul Townend, Thijs Metsch, Erik Elmroth:
When and How to Retrain Machine Learning-based Cloud Management Systems. 688-698 - Sohei Koyama, Osamu Tatebe:
Scalable Data Parallel Distributed Training for Graph Neural Networks. 699-707 - Benny J. Tang, Qiqi Chen, Matthew L. Weiss, Nathan C. Frey, Joseph McDonald, David Bestor, Charles Yee, William Arcand, William Bergeron, Chansup Byun, Daniel Edelman, Michael Houle, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Adam Michaleas, Peter Michaleas, Lauren Milechin, Julia S. Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Andrew Bowne, Lindsey McEvoy, Baolin Li, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi:
The MIT Supercloud Workload Classification Challenge. 708-714 - Dan Zhao, Nathan C. Frey, Vijay Gadepally, Siddharth Samsi:
Loss Curve Approximations for Fast Neural Architecture Ranking & Training Elasticity Estimation. 715-723 - Baolin Li, Vijay Gadepally, Siddharth Samsi, Devesh Tiwari:
Characterizing Multi-Instance GPU for Machine Learning Workloads. 724-731 - Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi:
Energy-aware neural architecture selection and hyperparameter optimization. 732-741 - Dan Zhao, Nathan C. Frey, Joseph McDonald, Matthew Hubbell, David Bestor, Michael Jones, Andrew Prout, Vijay Gadepally, Siddharth Samsi:
A Green(er) World for A.I. 742-750 - Georges Da Costa:
PDCO 2022 Keynote Talk: Performance and Energy models for modern HPC servers. 753 - Engelina L. Jenneskens, Rob H. Bisseling:
Exact k-way sparse matrix partitioning. 754-763 - Laleh Ghalami, Daniel Grosu:
A Family of Fast Parallel Greedy Algorithms for the Steiner Forest Problem. 764-773 - David R. Alves, Vijay K. Garg:
Parallel Minimum Spanning Tree Algorithms via Lattice Linear Predicate Detection. 774-782 - Tiago Carneiro, Loizos Koutsantonis, Nouredine Melab, Emmanuel Kieffer, Pascal Bouvry:
A Local Search for Automatic Parameterization of Distributed Tree Search Algorithms. 783-789 - Maxime Gobert, Jan Gmys, Jean-François Toubeau, Nouredine Melab, Daniel Tuyttens, François Vallée:
Parallel Bayesian Optimization for Optimal Scheduling of Underground Pumped Hydro-Energy Storage Systems. 790-797 - Jan Strappa, Paola Caymes-Scutari, Germán Bianchini:
A Parallel Novelty Search Metaheuristic Applied to a Wildfire Prediction System. 798-806 - Didier El Baz:
On Parallel or Distributed Asynchronous Iterations with Unbounded Delays and Possible Out of Order Messages or Flexible Communication for Convex Optimization Problems and Machine Learning. 807-813 - Sabine Roller, Peter Strazdins, Raphaël Couturier, Neda Ebrahimi Pour, Suzanne Michelle Shontz, Thomas Rauber, Gudula Rünger, Laurence T. Yang:
Message from the PDSEC-22 Workshop Chairs. 816-817 - Alexander Van Craen, Marcel Breyer, Dirk Pflüger:
PLSSVM: A (multi-)GPGPU-accelerated Least Squares Support Vector Machine. 818-827 - Jan Verschelde:
Least Squares on GPUs in Multiple Double Precision. 828-837 - Alex Fallin, Aarti Kothari, Jiayuan He, Christopher Yanez, Keshav Pingali, Rajit Manohar, Martin Burtscher:
A Simple, Fast, and GPU-friendly Steiner-Tree Heuristic. 838-847 - Subhash Saini, John Baron, Johnny Chang, Robert Hood, Haoqiang Jin:
Performance Evaluation of a Supercomputer Based on AMD Rome and Intel Cascade Lake Processors. 848-859 - Tatsuya Mitsuda, Kenji Ono:
A Scalable Parallel Partition Tridiagonal Solver for Many-Core and Low B/F Processors. 860-869 - Nawras Alnaasan, Arpan Jain, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems. 870-879 - Carl Pearson, Aurya Javeed, Karen D. Devine:
Machine Learning for CUDA+MPI Design Rules. 880-889 - Brice Goglin, Andrès Rubio Proaño:
Using Performance Attributes for Managing Heterogeneous Memory in HPC Applications. 890-899 - Médane A. Tchakorom, Raphaël Couturier, Jean-Claude Charr:
Synchronous parallel multisplitting method with convergence acceleration using a local Krylov-based minimization for solving linear systems. 900-906 - Christopher M. Siefert, Stephen L. Olivier, Gwendolyn Voskuilen, Jeffrey Young:
MultiGrid on FPGA Using Data Parallel C++. 907-910 - Che-Rung Lee, Satoshi Ohshima:
17th IEEE International Workshop on Automatic Performance Tuning (iWAPT2022). 911-912 - Arun V. Sathanur, Nathan R. Tallent, Patrick Konsor, Ken Koyanagi, Ryan McLaughlin, Joseph Olivas, Michael Chynoweth:
QuaL2 M: Learning Quantitative Performance of Latency-Sensitive Code. 913-923 - Aravind Sankaran, Navid Akbari Alashti, Christos Psarras, Paolo Bientinesi:
Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch. 924-933 - Reo Furuhata, Minglu Zhao, Keichi Takahashi, Yoichi Shimomura, Hiroyuki Takizawa:
Automated selection of build configuration based on machine learning. 934-941 - Yuta Sasaki, Keichi Takahashi, Yoichi Shimomura, Hiroyuki Takizawa:
A Cost Model for Compilers Based on Transfer Learning. 942-951 - William F. Godoy, Jenna Delozier, Gregory R. Watson:
Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications. 952-961 - Janaina Schwarzrock, Hiago Mayk G. de A. Rocha, Arthur Francisco Lorenzon, Antonio Carlos Schneider Beck:
Smoothing on Dynamic Concurrency Throttling. 962-971 - Jacob O. Tørring, Anne C. Elster:
Analyzing Search Techniques for Autotuning Image-based GPU Kernels: The Impact of Sample Sizes. 972-981 - Prashanthi S. K, Aakash Khochare, Sai Anuroop Kesanapalli, Rahul Atul Bhope, Yogesh Simmhan:
Don't Miss the Train: A Case for Systems Research into Training on the Edge. 985-986 - Ryan Dyson, Carlos Reaño:
Litener: An Accelerator-Enabled Lightweight Container for Edge Computing. 987-994 - Chandan Kumar, Yamini Mathur, Ali Jannesari:
Efficient Volume Estimation for Dynamic Environments using Deep Learning on the Edge. 995-1002 - Sam Leroux, Pieter Simoens, Meelis Lootus, Kartik Thakore, Akshay Sharma:
TinyMLOps: Operational Challenges for Widespread Edge AI Adoption. 1003-1010 - Pete Beckman, Emmanuel Jeannot, Swann Perarnau:
Workshop on Resource Arbitration for Dynamic Runtimes (RADR). 1011-1013 - Shingo Okuno, Akira Hirai, Naoto Fukumoto:
Performance Analysis of Multi-Containerized MD Simulations for Low-Level Resource Allocation. 1014-1017 - William White, Xiao Qin:
Operating System Convergence: An Example via the Maru OS Project. 1018-1027 - Amina Guermouche:
Combining Uncore Frequency and Dynamic Power Capping to Improve Power Savings. 1028-1037 - William Fornaciari:
ScaDL 2022 Invited Talk 1: Design of secure power monitors for accelerators, by exploiting ML techniques, in the Euro-HPC TEXTAROSSA project. 1039 - Mudhakar Srivatsa:
ScaDL 2022 Invited Talk 2: AI/ML Pipelines using CodeFlare. 1040 - Anima Anandkumar:
ScaDL 2022 Invited Talk 3: Million-x speedups through convergence of AI and HPC. 1041 - Michael Gschwind:
ScaDL 2022 Invited Talk 4: Sustainable AI @ Scale: Accelerating AI models for billions of users. 1042 - David Kanter:
When Moore Just Isn't Enough: Scaling ML in the Datacenter. 1043 - Barret Zoph:
Designing Effective Sparse Expert Models. 1044 - Josep Lluís Berral, Oriol Aranda, Juan Luis Domínguez, Jordi Torres:
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. 1045-1052 - Cèdric Prigent, Loïc Cudennec, Alexandru Costan, Gabriel Antoniu:
A Methodology to Build Decision Analysis Tools Applied to Distributed Reinforcement Learning. 1053-1062 - Olivier Beaumont, Lionel Eyraud-Dubois, Alena Shilova:
MadPipe: Memory Aware Dynamic Programming Algorithm for Pipelined Model Parallelism. 1063-1073 - Minseok Ryu, Youngdae Kim, Kibaek Kim, Ravi K. Madduri:
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. 1074-1083 - Zhen Xie, Siddhisanket Raskar, Murali Emani:
Throughput-oriented and Accuracy-aware DNN Training with BFloat16 on GPU. 1084-1087 - Yujing Ma, Florin Rusu, Kesheng Wu, Alexander Sim:
Adaptive Optimization for Sparse Data on Heterogeneous GPUs. 1088-1097 - Robert B. Ross:
ESSA 2022 Keynote Speaker: Keep Your Composure: HPC, Data Services, and the Mochi Project. 1100 - Johann Lombardi:
ESSA 2022 Invited Speaker DAOS: Nextgen Storage Stack for HPC and AI. 1101 - Lavanya Ramakrishnan:
ESSA 2022 Invited Speaker: The Curious Incident of the Data in the Scientific Workflow. 1102 - Osamu Tatebe, Hiroki Ohtsuji:
Caching Support for CHFS Node-local Persistent Memory File System. 1103-1110 - Chia-Ting Hung, Jerry Chou, Ming-Hung Chen, I-Hsin Chung:
A Locality-aware Cooperative Distributed Memory Caching for Parallel Data Analytic Applications. 1111-1117 - Grant Wilkins, Jon C. Calhoun:
Modeling Power Consumption of Lossy Compressed I/O for Exascale HPC Systems. 1118-1126 - John Korah, Eunice E. Santos:
6th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2022). 1127-1128 - Subhajit Sahu, Kishore Kothapalli, Dip Sankar Banerjee:
Dynamic Batch Parallel Algorithms for Updating PageRank. 1129-1138 - Ian Bogle, George M. Slota:
Distributed Algorithms for the Graph Biconnectivity and Least Common Ancestor Problems. 1139-1142 - Maxence Vandromme, Serge G. Petiton:
Efficient Parallel PageRank Algorithm for Network Analysis. 1143-1152 - Andreas Huber, Daniel Thilo Schroeder, Konstantin Pogorelov, Carsten Griwodz, Johannes Langguth:
A Streaming System for Large-scale Temporal Graph Mining of Reddit Data. 1153-1162 - Bhashithe Abeysinghe, Gyandeep Reddy Vulupala, Anu G. Bourgeois, Rajshekhar Sunderraman:
Unsupervised User Stance Detection on Tweets Against Web Articles Using Sentence Transformers. 1163-1169 - Vairavan Murugappan, Suresh Subramanian, John Korah, Pranav Pamidighantam, Eunice E. Santos:
Effect of Community-based Opinion Leaders on Guideline Dissemination in Large-Scale Physician Networks. 1170-1179 - David Z. Pan:
EDAML 2022 Keynote Speaker: Machine Learning for Agile, Intelligent and Open-Source EDA. 1181 - Ankush Sood:
EDAML 2022 Invited Speaker 1: Application of Machine Learning in High Level Synthesis. 1182 - Deming Chen:
EDAML 2022 Invited Speaker 2: AI Algorithm and Accelerator Co-design for Computing on the Edge. 1183 - R. Iris Bahar:
EDAML 2022 Invited Speaker 3: Scalable ML Architectures for Real-time Energy-efficient Computing. 1184 - Krishnendu Chakrabarty:
EDAML 2022 Invited Speaker 4: Fault Criticality Assessment in AI Accelerators. 1185 - Laleh Behjat:
EDAML 2022 Invited Speaker 5: Combining Optimization and Machine Learning in Physical Design. 1186 - Partha Pratim Pande:
EDAML 2022 Invited Speaker 6: Reliable Processing-in-Memory based Manycore Architectures for Deep Learning: From CNNs to GNNs. 1187 - Sachin S. Sapatnekar:
EDAML 2022 Invited Speaker 7: Analog and Digital Circuit and Layout Optimization using Machine Learning. 1188 - Muhammad Shafique:
EDAML 2022 Invited Speaker 8: Machine Learning for Cross-Layer Reliability and Security. 1189 - Sheldon X.-D. Tan:
EDAML 2022 Invited Speaker 9: Thermal and Power Monitoring and Estimation for Commercial Multicore Processors - A Machine Learning Perspective. 1190 - Sudeep Pasricha:
EDAML 2022 Invited Speaker 10: Hardware/Software Codesign for Optical Deep Learning Accelerators. 1191 - Paul Carpenter:
COMPSYS 2022 Keynote Talk: Composability at the Boundary Between HPC and Cloud. 1194 - Marc Taubenblatt, Asser N. Tantawi:
Quantifying Composable Data Center Utilization. 1195-1201 - Marcel Weisgut, Daniel Ritter, Martin Boissier, Michael Perscheid:
Separated Allocator Metadata in Disaggregated In-Memory Databases: Friend or Foe? 1202-1208 - Lance Long, Timothy Bargo, Luc Renambot, Maxine D. Brown, Andrew E. Johnson:
Composable Infrastructures for an Academic Research Environment: Lessons Learned. 1209-1214 - Zhongyi Chen, Luc Renambot, Lance Long, Maxine D. Brown, Andrew E. Johnson:
Moving from Composable to Programmable. 1215-1220 - Archit Patke, Haoran Qiu, Saurabh Jha, Srikumar Venugopal, Michele Gazzetti, Christian Pinto, Zbigniew Kalbarczyk, Ravishankar K. Iyer:
Evaluating Hardware Memory Disaggregation under Delay and Contention. 1221-1227 - Thomas Nowotny, James C. Knight:
CORtEX 2022 Invited Speaker 1: The GeNN ecosystem for GPU accelerated spiking neural network simulations. 1237 - Anders Lansner:
CORtEX 2022 Invited Speaker 2: Brain-like machine learning using BCPNN. 1238 - Oliver Rhodes:
CORtEX 2022 Invited Speaker 3: Neuromorphic computing: from modelling the brain to bio-inspired AI. 1239 - Jun Igarashi:
CORtEX 2022 Invited Speaker 4: Large-scale simulations of mammalian brains using peta- to exa-scale computing. 1240 - Lawrence Spracklen:
Controlling the spiraling costs of Deep Learning with the Neocortex. 1241 - Svitlana Volkova, Robert Rallo:
ExSAIS: Workshop on Extreme Scaling of AI for Science Message from the workshop chairs. 1242-1243 - Gennady Pekhimenko:
Keynote Talk 1: Efficient DNN Training at Scale: from Algorithms to Hardware. 1244 - Mostofa Patwary:
Keynote Talk 2 Training Large Language Models: Challenges and Opportunities. 1245 - Wayne Joubert, Bronson Messer, Philip C. Roth, Antigoni Georgiadou, Justin Lietz, Markus Eisenbach, Junqi Yin:
Learning to Scale the Summit: AI for Science on a Leadership Supercomputer. 1246-1255 - Sajal Dash, Benjamín Hernández, Aristeidis Tsaris, Folami T. Alamudun, Hong-Jun Yoon, Feiyi Wang:
A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems. 1266-1274 - Sanjukta Bhowmick, Anne-Cécile Orgerie:
IPDPS 2022 PhD Forum. 1275-1294
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