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ORCIDICS 2022: Virtual Event
- Lawrence Rauchwerger, Kirk W. Cameron, Dimitrios S. Nikolopoulos, Dionisios N. Pnevmatikatos:
ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28 - 30, 2022. ACM 2022, ISBN 978-1-4503-9281-5
Tools and modeling (I)
- Keren Zhou
, Jonathon M. Anderson, Xiaozhu Meng, John M. Mellor-Crummey:
Low overhead and context sensitive profiling of CPU-accelerated applications. 1:1-1:13 - Hossein Golestani, Rathijit Sen, Vinson Young, Gagan Gupta:
Calipers: a criticality-aware framework for modeling processor performance. 2:1-2:14 - Larissa Schmid, Marcin Copik, Alexandru Calotoiu, Dominik Werle, Andreas Reiter, Michael Selzer, Anne Koziolek, Torsten Hoefler:
Performance-detective: automatic deduction of cheap and accurate performance models. 3:1-3:13
New hardware technologies
- Cheng Tan, Thierry Tambe, Jeff Jun Zhang, Bo Fang, Tong Geng, Gu-Yeon Wei, David Brooks, Antonino Tumeo, Ganesh Gopalakrishnan, Ang Li:
ASAP: automatic synthesis of area-efficient and precision-aware CGRAs. 4:1-4:13 - Zixuan Ma, Haojie Wang, Guanyu Feng, Chen Zhang, Lei Xie, Jiaao He, Shengqi Chen, Jidong Zhai:
Efficiently emulating high-bitwidth computation with low-bitwidth hardware. 5:1-5:12 - Daeyoung Park, Heehoon Kim, Jinpyo Kim, Taehyun Kim, Jaejin Lee:
SnuQS: scaling quantum circuit simulation using storage devices. 6:1-6:13 - Ardhi Wiratama Baskara Yudha, Jake Meyer, Shougang Yuan, Huiyang Zhou, Yan Solihin:
LITE: a low-cost practical inter-operable GPU TEE. 7:1-7:13
Graph processing
- Hans Vandierendonck:
Software-defined floating-point number formats and their application to graph processing. 8:1-8:17 - Mohsen Koohi Esfahani, Peter Kilpatrick, Hans Vandierendonck:
MASTIFF: structure-aware minimum spanning tree/forest. 9:1-9:13 - Zhuoran Ji, Cho-Li Wang:
Efficient exact K-nearest neighbor graph construction for billion-scale datasets using GPUs with tensor cores. 10:1-10:12 - Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song:
Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems. 11:1-11:14
I/O and communication
- Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao:
CEAZ: accelerating parallel I/O via hardware-algorithm co-designed adaptive lossy compression. 12:1-12:13 - Mingzhe Liu, Haikun Liu, Chencheng Ye, Xiaofei Liao, Hai Jin, Yu Zhang, Ran Zheng, Liting Hu:
Towards low-latency I/O services for mixed workloads using ultra-low latency SSDs. 13:1-13:12 - Guangnan Feng, Dezun Dong, Yutong Lu:
Optimized MPI collective algorithms for dragonfly topology. 14:1-14:11
Compilers
- Adhitha Dias, Kirshanthan Sundararajah, Charitha Saumya, Milind Kulkarni:
SparseLNR: accelerating sparse tensor computations using loop nest restructuring. 15:1-15:14 - Sharjeel Khan, Bodhisatwa Chatterjee, Santosh Pande:
VICO: demand-driven verification for improving compiler optimizations. 16:1-16:14 - Alexandru Calotoiu, Tal Ben-Nun, Grzegorz Kwasniewski, Johannes de Fine Licht, Timo Schneider, Philipp Schaad, Torsten Hoefler:
Lifting C semantics for dataflow optimization. 17:1-17:13
Algorithms and accelerators
- Jinpyo Kim, Hyungdal Kwon, Jintaek Kang, Jihwan Park, Seungwook Lee, Jaejin Lee:
SnuHPL: high performance LINPACK for heterogeneous GPUs. 18:1-18:12 - Kamalakkannan Kamalavasan, Gihan R. Mudalige, István Z. Reguly, Suhaib A. Fahmy:
High throughput multidimensional tridiagonal system solvers on FPGAs. 19:1-19:12 - André Müller, Bertil Schmidt, Richard Membarth, Roland Leißa, Sebastian Hack:
AnySeq/GPU: a novel approach for faster sequence alignment on GPUs. 20:1-20:11 - Mohammad Almasri, Izzat El Hajj, Rakesh Nagi, Jinjun Xiong, Wen-Mei Hwu:
Parallel K-clique counting on GPUs. 21:1-21:14
Memory systems and memory management
- Apostolos Kokolis, Namrata Mantri, Shrikanth Ganapathy, Josep Torrellas, John Kalamatianos:
Cloak: tolerating non-volatile cache read latency. 22:1-22:13 - Hugo Tárrega, Alejandro Valero, Vicente Lorente, Salvador Petit, Julio Sahuquillo:
Fast-track cache: a huge racetrack memory L1 data cache. 23:1-23:12 - Minh Pham, Hao Li, Yongke Yuan, Chengcheng Mou, Kandethody Ramachandran, Zichen Xu, Yicheng Tu:
Dynamic memory management in massively parallel systems: a case on GPUs. 24:1-24:13 - Zhongzhe Hu, Junmin Xiao, Zheye Deng, Mingyi Li, Kewei Zhang, Xiaoyang Zhang, Ke Meng, Ninghui Sun, Guangming Tan:
MegTaiChi: dynamic tensor-based memory management optimization for DNN training. 25:1-25:13
Dense and sparse linear algebra
- Andy Nguyen, Ahmed E. Helal, Fabio Checconi, Jan Laukemann, Jesmin Jahan Tithi, Yongseok Soh, Teresa M. Ranadive, Fabrizio Petrini, Jee W. Choi:
Efficient, out-of-memory sparse MTTKRP on massively parallel architectures. 26:1-26:13 - Serif Yesil, José E. Moreira, Josep Torrellas:
Dense dynamic blocks: optimizing SpMM for processors with vector and matrix units using machine learning techniques. 27:1-27:14 - Xiaoyan Liu, Yi Liu, Hailong Yang, Jianjin Liao, Mingzhen Li, Zhongzhi Luan, Depei Qian:
Toward accelerated stencil computation by adapting tensor core unit on GPU. 28:1-28:12
Applications
- Taha Shahroodi, Mahdi Zahedi, Abhairaj Singh, Stephan Wong, Said Hamdioui:
KrakenOnMem: a memristor-augmented HW/SW framework for taxonomic profiling. 29:1-29:14 - Bagus Hanindhito, Dimitrios Gourounas, Arash Fathi, Dimitar Trenev, Andreas Gerstlauer, Lizy K. John:
GAPS: GPU-acceleration of PDE solvers for wave simulation. 30:1-30:13 - Arthur Francisco Lorenzon, Sandro Matheus V. N. Marques, Antoni C. Navarro, Vicenç Beltran:
Seamless optimization of the GEMM kernel for task-based programming models. 31:1-31:11
Tools and modeling (II)
- Wesley Smith, Aidan Goldfarb, Chen Ding:
Beyond time complexity: data movement complexity analysis for matrix multiplication. 32:1-32:12 - Andreas Abel, Jan Reineke:
uiCA: accurate throughput prediction of basic blocks on recent intel microarchitectures. 33:1-33:14 - Jonathon M. Anderson, Yumeng Liu, John M. Mellor-Crummey:
Preparing for performance analysis at exascale. 34:1-34:13 - Khalid Ayedh Alharthi, Arshad Jhumka, Sheng Di, Franck Cappello:
Clairvoyant: a log-based transformer-decoder for failure prediction in large-scale systems. 35:1-35:14
Machine learning
- Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler:
A data-centric optimization framework for machine learning. 36:1-36:13 - Shulai Zhang, Weihao Cui, Quan Chen, Zhengnian Zhang, Yue Guan, Jingwen Leng, Chao Li, Minyi Guo:
PAME: precision-aware multi-exit DNN serving for reducing latencies of batched inferences. 37:1-37:12 - Jiangsu Du, Jiazhi Jiang, Yang You, Dan Huang, Yutong Lu:
Handling heavy-tailed input of transformer inference on GPUs. 38:1-38:11 - Shihui Song, Peng Jiang:
Rethinking graph data placement for graph neural network training on multiple GPUs. 39:1-39:10
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