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Jiajia Li 0001
Person information
- affiliation: North Carolina State University, Raleigh, NC, USA
- affiliation (former): Pacific Northwest National Laboratory, Richland, WA, USA
- affiliation (former): Georgia Institute of Technology, Atlanta, GA, USA
Other persons with the same name
- Jiajia Li (aka: Jia-Jia Li, Jia-jia Li, JiaJia Li) — disambiguation page
- Jiajia Li 0002
— University of California at San Diego, La Jolla, CA, USA
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2020 – today
- 2024
- [c34]Keren Zhou
FASTEN: Fast GPU-accelerated Segmented Matrix Multiplication for Heterogenous Graph Neural Networks. ICS 2024: 511-524 - [c33]Guofeng Feng
POSTER: Optimizing Sparse Tensor Contraction with Revisiting Hash Table Design. PPoPP 2024: 457-459 - 2023
- [j9]Zheng Miao
Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition. ACM Trans. Parallel Comput. 10(2): 10:1-10:27 (2023) - [j8]Shruti Shivakumar
Sparse Symmetric Format for Tucker Decomposition. IEEE Trans. Parallel Distributed Syst. 34(6): 1743-1756 (2023) - [c32]Shruti Shivakumar, Ilya Amburg, Sinan G. Aksoy, Jiajia Li, Stephen J. Young
Fast Parallel Tensor Times Same Vector for Hypergraphs. HiPC 2023: 324-334 - [c31]Zhen Xie, Jie Liu, Jiajia Li
Merchandiser: Data Placement on Heterogeneous Memory for Task-Parallel HPC Applications with Load-Balance Awareness. PPoPP 2023: 204-217 - [i12]Shruti Shivakumar, Ilya Amburg, Sinan G. Aksoy, Jiajia Li, Stephen J. Young, Srinivas Aluru:
Fast Parallel Tensor Times Same Vector for Hypergraphs. CoRR abs/2311.08595 (2023) - 2022
- [c30]Zheng Miao, Jiajia Li
BALA-CPD: BALanced and Asynchronous Distributed Tensor Decomposition. CLUSTER 2022: 440-450 - [c29]Cheng Tan
DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs. HPCA 2022: 304-316 - [c28]Zhen Xie, Jie Liu, Sam Ma
LB-HM: load balance-aware data placement on heterogeneous memory for task-parallel HPC applications. PPoPP 2022: 435-436 - [c27]Zhen Du, Jiajia Li, Yinshan Wang, Xueqi Li, Guangming Tan, Ninghui Sun:
AlphaSparse: Generating High Performance SpMV Codes Directly from Sparse Matrices. SC 2022: 66:1-66:15 - [i11]Jieyang Chen, Chenhao Xie, Jesun Sahariar Firoz, Jiajia Li, Shuaiwen Leon Song, Kevin J. Barker
MSREP: A Fast yet Light Sparse Matrix Framework for Multi-GPU Systems. CoRR abs/2209.07552 (2022) - [i10]Zhen Du, Jiajia Li, Yinshan Wang, Xueqi Li, Guangming Tan, Ninghui Sun:
AlphaSparse: Generating High Performance SpMV Codes Directly from Sparse Matrices. CoRR abs/2212.10432 (2022) - 2021
- [c26]Shruti Shivakumar, Jiajia Li
Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors. ACDA 2021: 193-204 - [c25]Tong Geng, Chunshu Wu, Cheng Tan, Chenhao Xie, Anqi Guo, Pouya Haghi, Sarah Yuan He, Jiajia Li
A Survey: Handling Irregularities in Neural Network Acceleration with FPGAs. HPEC 2021: 1-8 - [c24]Cheng Tan, Tong Geng, Chenhao Xie, Nicolas Bohm Agostini
DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications. ICCD 2021: 33-40 - [c23]Chenhao Xie, Jieyang Chen
Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. ICPP 2021: 53:1-53:11 - [c22]Jiawen Liu, Dong Li, Roberto Gioiosa, Jiajia Li
Athena: high-performance sparse tensor contraction sequence on heterogeneous memory. ICS 2021: 190-202 - [c21]Ruiqin Tian, Luanzheng Guo, Jiajia Li
A High Performance Sparse Tensor Algebra Compiler in MLIR. LLVM-HPC@SC 2021: 27-38 - [c20]Jiawen Liu, Jie Ren
Sparta: high-performance, element-wise sparse tensor contraction on heterogeneous memory. PPoPP 2021: 318-333 - [i9]Ruiqin Tian, Luanzheng Guo, Jiajia Li, Bin Ren, Gokcen Kestor:
A High-Performance Sparse Tensor Algebra Compiler in Multi-Level IR. CoRR abs/2102.05187 (2021) - 2020
- [j7]Eric R. Hein, Srinivas Eswar
Programming Strategies for Irregular Algorithms on the Emu Chick. ACM Trans. Parallel Comput. 7(4): 25:1-25:25 (2020) - [j6]Ang Li
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. IEEE Trans. Parallel Distributed Syst. 31(1): 94-110 (2020) - [c19]Jesun Sahariar Firoz, Ang Li, Jiajia Li
On the Feasibility of Using Reduced-Precision Tensor Core Operations for Graph Analytics. HPEC 2020: 1-7 - [c18]Jiajia Li
A Sparse Tensor Benchmark Suite for CPUs and GPUs. IISWC 2020: 193-204 - [c17]Jiajia Li
A parallel sparse tensor benchmark suite on CPUs and GPUs. PPoPP 2020: 403-404 - [i8]Jiajia Li, Mahesh Lakshminarasimhan, Xiaolong Wu, Ang Li, Catherine Olschanowsky, Kevin J. Barker:
A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs. CoRR abs/2001.00660 (2020) - [i7]Chenhao Xie, Jieyang Chen, Jesun Sahariar Firoz, Jiajia Li, Shuaiwen Leon Song, Kevin J. Barker, Mark Raugas, Ang Li:
Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. CoRR abs/2012.06959 (2020)
2010 – 2019
- 2019
- [j5]Jiajia Li
PASTA: a parallel sparse tensor algorithm benchmark suite. CCF Trans. High Perform. Comput. 1(2): 111-130 (2019) - [j4]Yuchen Ma
Optimizing sparse tensor times matrix on GPUs. J. Parallel Distributed Comput. 129: 99-109 (2019) - [j3]Jeffrey S. Young, Eric R. Hein, Srinivas Eswar
A microbenchmark characterization of the Emu chick. Parallel Comput. 87: 60-69 (2019) - [c16]Jiajia Li
Efficient and effective sparse tensor reordering. ICS 2019: 227-237 - [c15]Israt Nisa, Jiajia Li
Load-Balanced Sparse MTTKRP on GPUs. IPDPS 2019: 123-133 - [c14]Ke Meng, Jiajia Li
A pattern based algorithmic autotuner for graph processing on GPUs. PPoPP 2019: 201-213 - [c13]Israt Nisa, Jiajia Li
An efficient mixed-mode representation of sparse tensors. SC 2019: 49:1-49:25 - [i6]Eric R. Hein, Srinivas Eswar, Abdurrahman Yasar, Jiajia Li, Jeffrey S. Young, Thomas M. Conte, Ümit V. Çatalyürek, Rich Vuduc, E. Jason Riedy, Bora Uçar:
Programming Strategies for Irregular Algorithms on the Emu Chick. CoRR abs/1901.02775 (2019) - [i5]Jiajia Li, Yuchen Ma
PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite. CoRR abs/1902.03317 (2019) - [i4]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. CoRR abs/1903.04611 (2019) - [i3]Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Richard W. Vuduc, P. Sadayappan:
Load-Balanced Sparse MTTKRP on GPUs. CoRR abs/1904.03329 (2019) - 2018
- [b1]Jiajia Li:
Scalable tensor decompositions in high performance computing environments. Georgia Institute of Technology, Atlanta, GA, USA, 2018 - [j2]Guangming Tan, Junhong Liu
Design and Implementation of Adaptive SpMV Library for Multicore and Many-Core Architecture. ACM Trans. Math. Softw. 44(4): 46:1-46:25 (2018) - [j1]Junhong Liu
An Autotuning Protocol to Rapidly Build Autotuners. ACM Trans. Parallel Comput. 5(2): 9:1-9:25 (2018) - [c12]Eric R. Hein, Tom Conte
An Initial Characterization of the Emu Chick. IPDPS Workshops 2018: 579-588 - [c11]Yue Zhao, Jiajia Li
Bridging the gap between deep learning and sparse matrix format selection. PPoPP 2018: 94-108 - [c10]Jiajia Li, Jimeng Sun, Richard W. Vuduc:
HiCOO: hierarchical storage of sparse tensors. SC 2018: 19:1-19:15 - [i2]Jeffrey Young, Eric R. Hein, Srinivas Eswar, Patrick Lavin, Jiajia Li, E. Jason Riedy, Richard W. Vuduc, Tom Conte:
A Microbenchmark Characterization of the Emu Chick. CoRR abs/1809.07696 (2018) - 2017
- [c9]Yue Zhao, Jiajia Li, Chunhua Liao, Xipeng Shen:
POSTER: Bridging the Gap Between Deep Learning and Sparse Matrix Format Selection. PACT 2017: 152-153 - [c8]Jiajia Li
Model-Driven Sparse CP Decomposition for Higher-Order Tensors. IPDPS 2017: 1048-1057 - [c7]Xiuxia Zhang, Guangming Tan, Shuangbai Xue, Jiajia Li
Understanding the GPU Microarchitecture to Achieve Bare-Metal Performance Tuning. PPoPP 2017: 31-43 - 2016
- [c6]Jiajia Li
Optimizing Sparse Tensor Times Matrix on Multi-core and Many-Core Architectures. IA3@SC 2016: 26-33 - 2015
- [c5]B. Neelima, Jiajia Li
Introducing high performance computing concepts into engineering undergraduate curriculum: a success story. EduHPC@SC 2015: 6:1-6:8 - [c4]Jiajia Li
An input-adaptive and in-place approach to dense tensor-times-matrix multiply. SC 2015: 76:1-76:12 - 2013
- [c3]Jiajia Li
SMAT: an input adaptive auto-tuner for sparse matrix-vector multiplication. PLDI 2013: 117-126 - 2012
- [c2]Jiajia Li
An optimized large-scale hybrid DGEMM design for CPUs and ATI GPUs. ICS 2012: 377-386 - [i1]Jiajia Li, Xiuxia Zhang, Guangming Tan, Mingyu Chen:
SMAT: An Input Adaptive Sparse Matrix-Vector Multiplication Auto-Tuner. CoRR abs/1210.2536 (2012) - 2010
- [c1]Jiajia Li
Automatically Tuned Dynamic Programming with an Algorithm-by-Blocks. ICPADS 2010: 452-459
Coauthor Index
aka: Rich Vuduc
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