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UID:submissions.supercomputing.org_SC24_sess745@linklings.com
SUMMARY:15th Workshop on Latest Advances in Scalable Algorithms for Large-
 Scale Heterogeneous Systems (ScalAH'24)
DESCRIPTION:Novel hybrid scalable scientific algorithms are needed with th
 e advent of variety of novel accelerators including GPUs and FPGAs, as wel
 l as with the growth of the size of the Quantum Computing Devices and neur
 omorphic chips and various AI specific processors. This myriad of devices 
 requires a unified approach that allows efficient and scalable hybrid appr
 oaches combining classical and novel computing paradigms to be implemented
  at scale. These extreme-scale heterogeneous systems require these novel s
 cientific algorithms to hide the complexity, hide network and memory laten
 cy, have advanced communication, and have no synchronization points where 
 possible. With the advent of AI in the past few years the need of such sca
 lable mathematical methods and algorithms for such hybrid architectures th
 at are able to handle data and compute-intensive applications at scale bec
 omes even more important.\n\nInvited Talk: Mapping Irregular Computations 
 to Accelerator-Based Exascale Systems\n\nAs traditional technology drivers
  of computing performance level off, the use of accelerators with various 
 levels of specialization, are growing in importance. At the same time, dat
 a movement continues to dominate running time and energy costs, making com
 munication cost reduction the primary optimiz...\n\n\nKatherine Yelick (Un
 iversity of California, Berkeley; Lawrence Berkeley National Laboratory (L
 BNL))\n---------------------\nAn Ising-based Decision Method for Intra Pre
 diction Mode in Video Coding\n\nVideo AI and transmission are used in vari
 ous fields.  Video compression is based on many combinatorial optimization
  problems.  It is difficult for conventional computers to solve problems b
 ecause these problems take exponential time as the problem size increases.
  To solve these problems, Ising mach...\n\n\nTakuto Momominami and Naoya N
 iwa (Tokyo University of Agriculture and Technology); Masahito Kumagai, Ka
 zuhiko Komatsu, and Hiroaki Kobayashi (Tohoku University); and Hiroe Iwasa
 ki (Tokyo University of Agriculture and Technology, Tohoku University)\n--
 -------------------\nInvited Talk: Neuromorphic Computing: From Edge to HP
 C\n\nNeuromorphic computing is a popular technology for the future of comp
 uting.  Neuromorphic systems have the opportunity to impact computing from
  the edge to HPC-scale systems. In this talk, I will overview the field of
  neuromorphic computing with a particular focus on challenges and opportun
 ities in ...\n\n\nCatherine Schuman (University of Tennessee, Knoxville)\n
 ---------------------\nAccelerating an overhead-sensitive atmospheric mode
 l on GPUs using asynchronous execution and kernel fusion\n\nMethods to mit
 igate the kernel launch overhead, one of drawbacks of GPUs, were implement
 ed to an overhead-sensitive atmospheric model using OpenACC and CUDA and w
 ere evaluated. OpenACC enables kernels to run asynchronously in either one
  or multiple GPU queues. Moreover, CUDA allows different loops t...\n\n\nK
 azuya Yamazaki (The University of Tokyo, Japan)\n---------------------\nSc
 alAH'24 — Afternoon Break\n---------------------\nA Performance Portable M
 ulti-GPU Implementation of 3D Euler Equations using ProtoX and IRIS\n\nDom
 ain scientists in the field of computational science often face challenges
  in developing optimized code for high-performance computing, especially G
 PUs. Considering the increase of heterogeneity in a node of HPC computing 
 facilities, there is a demand to develop performance portable solutions fo
 r...\n\n\nHet Mankad and Mohammad Alaul Haque Monil (Oak Ridge National La
 boratory (ORNL)), Sanil Rao (Carnegie Mellon University), Phillip Colella 
 and Brian Van Straalen (Lawrence Berkeley National Laboratory (LBNL)), Fra
 nz Franchetti (Carnegie Mellon University), and Jeffrey Vetter (Oak Ridge 
 National Laboratory (ORNL))\n---------------------\nHigh-Performance Eigen
 Solver Combining EigenExa and Iterative Refinement\n\nThis study proposes 
 a high-performance and reliable eigensolver via mixed-precision arithmetic
  between ordinary and highly-accurate precisions. Eigenvalue decomposition
  is ubiquitous in simulations. Various eigensolvers for computing approxim
 ations have been developed thus far. If eigenvalues are na...\n\n\nYuki Uc
 hino and Toshiyuki Imamura (RIKEN)\n---------------------\nSequences of Di
 stributed Matrix-Vector Product for Very Large and Very Sparse Irregular M
 atrices\n\nWe study the performance behavior of the sparse matrix-vector p
 roduct operation in distributed computing environments, in the case of ver
 y large non-diagonal matrices where the nonzero elements are placed irregu
 larly across the matrix. In particular, we focus on the distributed storag
 e of the result...\n\n\nMaxence Vandromme, Nicolas Hochart, and Serge G. P
 etiton (University of Lille, France); Jérôme Gurhem (Maison de la Simulati
 on); and Miwako Tsuji and Mitsuhisa Sato (RIKEN)\n---------------------\nL
 everaging Hybrid Classical-Quantum Methods for Efficient Load Rebalancing 
 in HPC\n\nLoad balancing (LB) is a challenge for parallel applications in 
 High Performance Computing (HPC). Depending on various constraints, LB is 
 an optimization problem. This paper focuses on the context of a given task
  distribution in distributed memory systems, where load imbalance might ha
 ppen at runtim...\n\n\nJustyna Zawalska (AGH University of Krakow, ACC Cyf
 ronet AGH); Minh Chung (Leibniz Supercomputing Centre (LRZ); MNM-Team, Lud
 wig-Maximilians-Universität München); Katarzyna Rycerz (AGH University of 
 Krakow, ACC Cyfronet AGH); Laura Schulz and Martin Schulz (Leibniz Superco
 mputing Centre (LRZ)); and Dieter Kranzlmüller (Ludwig-Maxmilians-Universi
 tät München, Leibniz Supercomputing Centre (LRZ))\n\nTag: Algorithms, Hete
 rogeneous Computing\n\nRegistration Category: Workshop Reg Pass\n\nSession
  Chairs: Vassil Alexandrov (Hartree Centre, STFC); Jack Dongarra (Universi
 ty of Tennessee, Knoxville; Oak Ridge National Laboratory (ORNL)); Erik Dr
 aeger (Lawrence Livermore National Laboratory (LLNL), Center for Applied S
 cientific Computing); Christian Engelmann (Oak Ridge National Laboratory (
 ORNL)); and Dieter A. Kranzlmueller (Ludwig-Maxmilians-Universität München
 , Leibniz Supercomputing Centre (LRZ))
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