Search Results - Mathematics of computing Mathematical analysis Numerical analysis Computations on matrices

Trapezoid: A Versatile Accelerator for Dense and Sparse Matrix Multiplications by Yang, Yifan, Emer, Joel S., Sanchez, Daniel

“…Accelerating matrix multiplication is crucial to achieve high performance in many application domains, including neural networks, graph analytics, and scientific computing…”
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InnerSP: A Memory Efficient Sparse Matrix Multiplication Accelerator with Locality-Aware Inner Product Processing by Baek, Daehyeon, Hwang, Soojin, Heo, Taekyung, Kim, Daehoon, Huh, Jaehyuk

“…Sparse matrix multiplication is one of the key computational kernels in large-scale data analytics…”
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ReSMiPS: A ReRAM-based Sparse Mixed-precision Solver with Fast Matrix Reordering Algorithm by Fu, Yuyang, Li, Jiancong, Chen, Jia, Zhou, Zhiwei, Zhou, Houji, Peng, Wenlong, Li, Yi, Miao, Xiangshui

“…The solution of sparse matrix equations is essential in scientific computing. However, traditional solvers on digital computing platforms are limited by memory bottlenecks in largescale sparse matrix storage and computation…”
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Pipirima: Predicting Patterns in Sparsity to Accelerate Matrix Algebra by Bakhtiar, Ubaid, Joo, Donghyeon, Asgari, Bahar

“…While sparsity, a feature of data in many applications, provides optimization opportunities such as reducing unnecessary computations, data transfers, and storage, it causes several challenges, too…”
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pSyncPIM: Partially Synchronous Execution of Sparse Matrix Operations for All-Bank PIM Architectures by Baek, Daehyeon, Hwang, Soojin, Huh, Jaehyuk

“… Sparse matrix processing is another critical computation that can significantly benefit from the PIM architecture, but the current all-bank PIM control cannot support diverging executions due to the random sparsity…”
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An Input-Aware Sparse Tensor Compiler Empowered by Vectorized Acceleration by He, Xianhao, Wang, Haotian, Zhang, Jiapeng, Yang, Wangdong, Chronopoulos, Anthony Theodore, Li, Kenli

“… Sparse matrix-matrix multiplication (SpMM) is a representative operator in sparse computations, whose performance is often limited by the design of sparse formats and the extent of hardware architecture optimization…”
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Tackling the Matrix Multiplication Micro-Kernel Generation with Exo by Castello, Adrian, Bellavita, Julian, Dinh, Grace, Ikarashi, Yuka, Martinez, Hector

“…The optimization of the matrix multiplication (or GEMM) has been a need during the last decades…”
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SSpMV: A Sparsity-aware SpMV Framework Empowered by Multimodal Machine Learning by Lin, Shengle, Liu, Chubo, Ding, Yan, Zhou, Joey Tianyi, Li, Kenli, Yang, Wangdong

“…Sparse Matrix-Vector Multiplication (SpMV) is an essential sparse operation in scientific computing and artificial intelligence…”
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Me-MPK: Accelerating Krylov Subspace Solvers via Memory-efficient Matrix-Power Kernel by Qiu, Haozhong, Xu, Chuanfu, Fang, Jianbin, Li, Shengguo, Deng, Liang, Zhang, Jian, Dai, Zhe, Ding, Yue, Wang, Yue, Han, Zhimeng, Che, Yonggang, Liu, Jie

“…This paper focuses on optimizing the Matrix-Power Kernel (MPK), which relies on a series of Sparse Matrix-Vector multiplications (SpMVs…”
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JITSPMM: Just-in-Time Instruction Generation for Accelerated Sparse Matrix-Matrix Multiplication by Fu, Qiang, Rolinger, Thomas B., Huang, H. Howie

“…Achieving high performance for Sparse Matrix-Matrix Multiplication (SpMM) has received increasing research attention, especially on multi-core CPUs, due to the large input data size in applications such as graph neural networks (GNNs…”
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SpV8: Pursuing Optimal Vectorization and Regular Computation Pattern in SpMV by Li, Chenyang, Xia, Tian, Zhao, Wenzhe, Zheng, Nanning, Ren, Pengju

“… Specifically, SpV8 analyzes data distribution in different matrices and row panels, and accordingly applies optimization method that achieves the maximal vectorization with regular computation patterns…”
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FSPA: An FeFET-based Sparse Matrix-Dense Vector Multiplication Accelerator by Zhang, Xiaoyu, Li, Zerun, Liu, Rui, Chen, Xiaoming, Han, Yinhe

“…Sparse matrix-dense vector multiplication (SpMV) is widely used in various applications…”
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Numerically-Stable and Highly-Scalable Parallel LU Factorization for Circuit Simulation by Chen, Xiaoming

“… The coefficient matrices of these linear systems have the identical structure but different values…”
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A Methodology for Characterizing Sparse Datasets and Its Application to SIMD Performance Prediction by Zhu, Gangyi, Jiang, Peng, Agrawal, Gagan

“…Irregular computations are commonly seen in many scientific and engineering domains that use unstructured meshes or sparse matrices…”
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Red-Blue Pebbling Revisited: Near Optimal Parallel Matrix-Matrix Multiplication by Kwasniewski, Grzegorz, Kabic, Marko, Besta, Maciej, VandeVondele, Joost, Solca, Raffaele, Hoefler, Torsten

“…We propose COSMA: a parallel matrix-matrix multiplication algorithm that is near communication-optimal for all combinations of matrix dimensions, processor counts, and memory sizes…”
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A data locality-aware design framework for reconfigurable sparse matrix-vector multiplication kernel by Sicheng Li, Yandan Wang, Wujie Wen, Yu Wang, Yiran Chen, Hai Li

“…Sparse matrix-vector multiplication (SpMV) is an important computational kernel in many applications…”
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A tensor-based volterra series black-box nonlinear system identification and simulation framework by Batselier, Kim, Zhongming Chen, Haotian Liu, Ngai Wong

“…Tensors are a multi-linear generalization of matrices to their d-way counterparts, and are receiving intense interest recently due to their natural representation of high-dimensional data…”
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Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices by Krishnaswamy, Smita, Viamontes, George F., Markov, Igor L., Hayes, John P.

“…Soft errors are an increasingly serious problem for logic circuits. To estimate the effects of soft errors on such circuits, we develop a general computational framework based on probabilistic transfer matrices (PTMs…”
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Solvability of Matrix-Exponential Equations by Ouaknine, Joel, Pouly, Amaury, Sousa-Pinto, Joao, Worrell, James

“…We consider a continuous analogue of (Babai et al. 1996)'s and (Cai et al. 2000)'s problem of solving multiplicative matrix equations. Given k…”
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SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library by Gates, Mark, Kurzak, Jakub, Charara, Ali, YarKhan, Asim, Dongarra, Jack

“… SLATE uses modern techniques such as communication-avoiding algorithms, lookahead panels to overlap communication and computation, and task-based scheduling, along with a modern C++ framework…”
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