10 citations · 18 across the 7 of their papers we have counts for
10 papers
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…