1 citations · 2 across the 14 of their papers we have counts for
14 papers
CFP: Efficient Optimization of Intra-Operator Parallelism Plans for Large Model Training
Weifang Hu, Xuanhua Shi, Yunkai Zhang +7
Optimizing the parallel training of large models requires exploring intra-operator parallelism plans for a computation graph that typically contains tens of thousands of primitive…
gECC: A GPU-based high-throughput framework for Elliptic Curve Cryptography
Qian Xiong, Weiliang Ma, Xuanhua Shi +5
Elliptic Curve Cryptography (ECC) is an encryption method that provides security comparable to traditional techniques like Rivest-Shamir-Adleman (RSA) but with lower computational…
Hyperbolic Hypergraph Neural Networks for Multi-Relational Knowledge Hypergraph Representation
Mengfan Li, Xuanhua Shi, Chenqi Qiao +2
Knowledge hypergraphs generalize knowledge graphs using hyperedges to connect multiple entities and depict complicated relations. Existing methods either transform hyperedges into…
Generalization-Enhanced Code Vulnerability Detection via Multi-Task Instruction Fine-Tuning
Xiaohu Du, Ming Wen, Jiahao Zhu +5
Code Pre-trained Models (CodePTMs) based vulnerability detection have achieved promising results over recent years. However, these models struggle to generalize as they typically l…
Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback
Zhangqian Bi, Yao Wan, Zheng Wang +7
Large Language Models (LLMs) have shown remarkable progress in automated code generation. Yet, LLM-generated code may contain errors in API usage, class, data structure, or missing…
Graph for Science: From API based Programming to Graph Engine based Programming for HPC
Yu Zhang, Zixiao Wang, Jin Zhao +5
Modern scientific applications predominantly run on large-scale computing platforms, necessitating collaboration between scientific domain experts and high-performance computing (H…
Scalable Optimal Margin Distribution Machine
Yilin Wang, Nan Cao, Teng Zhang +2
Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performanc…
Multi-Stage Network Embedding for Exploring Heterogeneous Edges
Hong Huang, Yu Song, Fanghua Ye +3
The relationships between objects in a network are typically diverse and complex, leading to the heterogeneous edges with different semantic information. In this paper, we focus on…
Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction
Zhexue Chen, Hong Huang, Bang Liu +2
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining…
Modeling Heterogeneous Edges to Represent Networks with Graph Auto-Encoder
Lu Wang, Yu Song, Hong Huang +3
In the real world, networks often contain multiple relationships among nodes, manifested as the heterogeneity of the edges in the networks. We convert the heterogeneous networks in…
Optimizing the SSD Burst Buffer by Traffic Detection
Xuanhua Shi, Wei Liu, Ligang He +3
Currently, Burst buffer has been proposed to manage the SSD buffering of bursty write requests. Although burst buffer can improve I/O performance in many cases, we find that it has…
MURS: Mitigating Memory Pressure in Service-oriented Data Processing Systems
Xuanhua Shi, Xiong Zhang, Ligang He +3
Although a data processing system often works as a batch processing system, many enterprises deploy such a system as a service, which we call the service-oriented data processing s…
Core Maintenance in Dynamic Graphs: A Parallel Approach based on Matching
Na Wang, Dongxiao Yu, Hai Jin +3
The core number of a vertex is a basic index depicting cohesiveness of a graph, and has been widely used in large-scale graph analytics. In this paper, we study the update of core…
Lifetime-Based Memory Management for Distributed Data Processing Systems
Lu Lu, Xuanhua Shi, Yongluan Zhou +5
In-memory caching of intermediate data and eager combining of data in shuffle buffers have been shown to be very effective in minimizing the re-computation and I/O cost in distribu…