Ping Xiang

Works (5)

Updated: July 5th, 2023 15:47

2014 conference paper

Warp-level divergence in GPUs: Characterization, impact, and mitigation

International symposium on high-performance computer, 284–295.

By: P. Xiang n, Y. Yang & Huiyang

TL;DR: This paper proposes to allocate and release resources at the warp level, which effectively increase the number of active warps without actually increasing the size of critical resources, and presents its lightweight architectural support for the proposed warp-level resource management. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2013 journal article

Locality principle revisited: A probability-based quantitative approach

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 73(7), 1011–1027.

By: S. Gupta n, P. Xiang n, Y. Yang n & H. Zhou n 

author keywords: Locality of references; Probability; Memory hierarchy; Last level cache; Cache replacement policy; Data prefetching; Locality optimizations
TL;DR: This paper revisits the fundamental concept of the locality of references and proposes to quantify it as a conditional probability: in an address stream, how likely the same address or an address within its neighborhood will be accessed in the near future is defined. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2012 conference paper

CPU-assisted GPGPU on fused CPU-GPU architectures

International symposium on high-performance computer, 103–114.

By: Y. Yang, P. Xiang, M. Mantor & H. Zhou 

Source: NC State University Libraries
Added: August 6, 2018

2012 conference paper

Locality principle revisited: A probability-based quantitative approach

2012 ieee 26th international parallel and distributed processing symposium (ipdps), 995–1009.

By: S. Gupta n, P. Xiang n, Y. Yang n & Huiyang

UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (Web of Science; OpenAlex)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2010 article

An Optimizing Compiler for GPGPU Programs with Input-Data Sharing

PPOPP 2010: PROCEEDINGS OF THE 2010 ACM SIGPLAN SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING, pp. 343–344.

By: Y. Yang n, P. Xiang*, J. Kong* & H. Zhou n 

author keywords: GPGPU; Compiler
TL;DR: A novel compiler to optimize GPGPU programs is introduced, which takes a naive GPU kernel function, which is functionally correct but without any consideration for performance optimization, and generates optimized code. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

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