305 citations · 327 across the 10 of their papers we have counts for
11 papers
AlphaSparse: Generating High Performance SpMV Codes Directly from Sparse Matrices
Zhen Du, Jiajia Li, Yinshan Wang +3
Sparse Matrix-Vector multiplication (SpMV) is an essential computational kernel in many application scenarios. Tens of sparse matrix formats and implementations have been proposed…
MSREP: A Fast yet Light Sparse Matrix Framework for Multi-GPU Systems
Jieyang Chen, Chenhao Xie, Jesun S Firoz +5
Sparse linear algebra kernels play a critical role in numerous applications, covering from exascale scientific simulation to large-scale data analytics. Offloading linear algebra k…
A High-Performance Sparse Tensor Algebra Compiler in Multi-Level IR
Ruiqin Tian, Luanzheng Guo, Jiajia Li +2
Tensor algebra is widely used in many applications, such as scientific computing, machine learning, and data analytics. The tensors represented real-world data are usually large an…
Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures
Chenhao Xie, Jieyang Chen, Jesun S Firoz +5
Designing efficient and scalable sparse linear algebra kernels on modern multi-GPU based HPC systems is a daunting task due to significant irregular memory references and workload…
A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs
Jiajia Li, Mahesh Lakshminarasimhan, Xiaolong Wu +3
Tensor computations present significant performance challenges that impact a wide spectrum of applications ranging from machine learning, healthcare analytics, social network analy…
Load-Balanced Sparse MTTKRP on GPUs
Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam +2
Sparse matricized tensor times Khatri-Rao product (MTTKRP) is one of the most computationally expensive kernels in sparse tensor computations. This work focuses on optimizing the M…
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
Ang Li, Shuaiwen Leon Song, Jieyang Chen +4
High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and…
PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite
Jiajia Li, Yuchen Ma, Xiaolong Wu +2
Tensor methods have gained increasingly attention from various applications, including machine learning, quantum chemistry, healthcare analytics, social network analysis, data mini…
Programming Strategies for Irregular Algorithms on the Emu Chick
Eric Hein, Srinivas Eswar, Abdurrahman Yaşar +7
The Emu Chick prototype implements migratory memory-side processing in a novel hardware system. Rather than transferring large amounts of data across the system interconnect, the E…
A Microbenchmark Characterization of the Emu Chick
Jeffrey S. Young, Eric Hein, Srinivas Eswar +5
The Emu Chick is a prototype system designed around the concept of migratory memory-side processing. Rather than transferring large amounts of data across power-hungry, high-latenc…
SMAT: An Input Adaptive Sparse Matrix-Vector Multiplication Auto-Tuner
Jiajia Li, Xiuxia Zhang, Guangming Tan +1
Sparse matrix vector multiplication (SpMV) is an important kernel in scientific and engineering applications. The previous optimizations are sparse matrix format specific and expos…