Xiaoming Li

发表

Analyzing the Uses of a Software Modeling Tool

Sarfraz Khurshid, Darko Marinov, Xiaoming Li, 2006, Electron. Notes Theor. Comput. Sci..

ASUPPA : A FRAMEWORK FOR INTERACTIVE AND ITERATIVE SYNTHESIS AND IMPROVEMENT OF PROCESS PLANS

Xiaoming Li, 2002 .

Process Planner's Assistant: an Interactive and Iterative Approach to Automating Process Planning

Xiaoming Li, 1997 .

Chiplets and the Codelet Model

Xiaoming Li, J. M. Diaz, D. Fox, 2022, ArXiv.

Fast Convolutional Neural Networks with Fine-Grained FFTs

Xiaoming Li, Yulin Zhang, Xiaoming Li, 2020, PACT.

Optimizing Sorting with Machine Learning Algorithms

David A. Padua, Xiaoming Li, María Jesús Garzarán, 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

Machine Learning Techniques for Code Generation and Optimization

Xiaoming Li, David Padua, D. Padua, 2006 .

Optimizing sorting with genetic algorithms

David A. Padua, Xiaoming Li, María Jesús Garzarán, 2005, International Symposium on Code Generation and Optimization.

A dynamically tuned sorting library

David A. Padua, Xiaoming Li, María Jesús Garzarán, 2004, International Symposium on Code Generation and Optimization, 2004. CGO 2004..

CUDA Memory Optimizations for Large Data-Structures in the Gravit Simulator

Xiaoming Li, Jakob Siegel, Juergen Ributzka, 2009, 2009 International Conference on Parallel Processing Workshops.

CSSMT: Compiler Based Software Simultaneous Multithreading (SMT)

Yuanfang Chen, Xiaoming Li, Qingchuan Shi, 2018, 2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).

A Thread Merging Transformation to Improve Throughput of Multiple Programs

Yuanfang Chen, Xiaoming Li, Xiaoming Li, 2015, 2015 IEEE 29th International Conference on Advanced Information Networking and Applications.

Is Search Really Necessary to Generate High-Performance BLAS?

Gang Ren, David A. Padua, Keshav Pingali, 2005, Proceedings of the IEEE.

Context-aware code optimization

Xiaoming Li, Murat Bolat, Xiaoming Li, 2009, 2009 IEEE 28th International Performance Computing and Communications Conference.

A comparison of empirical and model-driven optimization

Gang Ren, David A. Padua, Gerald DeJong, 2003, PLDI '03.

A Dataflow Programming Language and its Compiler for Streaming Systems

Guang R. Gao, Haitao Wei, Xiaoming Li, 2014, ICCS.

Analytic Models and Empirical Search: A Hybrid Approach to Code Optimization

Gang Ren, David A. Padua, Gerald DeJong, 2005, LCPC.

Optimizing Matrix Multiplication with a Classifier Learning System

Xiaoming Li, María Jesús Garzarán, Xiaoming Li, 2005, LCPC.

DFT Performance Prediction in FFTW

Liang Gu, Xiaoming Li, Xiaoming Li, 2009, LCPC.

An Empirically Optimized Radix Sort for GPU

Xiaoming Li, Jinlan Gao, Bonan Huang, 2009, 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications.

Automatic generation of a parallel sorting algorithm

David A. Padua, Xiaoming Li, María Jesús Garzarán, 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

Experience of Optimizing FFT on Intel Architectures

Guang R. Gao, Liping Xue, Xiaoming Li, 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

A control-structure splitting optimization for GPGPU

Xiaoming Li, Snaider Carrillo, Jakob Siegel, 2009, CF '09.

Efficient sparse matrix-matrix multiplication on heterogeneous high performance systems

Sriram Krishnamoorthy, Antonino Tumeo, Xiaoming Li, 2010, 2010 IEEE International Conference On Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS).

Impact analysis of conditional and loop statements for the NVIDIA G80 architecture

Snaider Carrillo, Xiaoming Li, Jakob Siegel, 2010 .

Source Code Partitioning in Program Optimization

Guang R. Gao, Xiaoming Li, Kirk Kelsey, 2011, 2011 IEEE 17th International Conference on Parallel and Distributed Systems.

Computer Architecture and Parallel Systems Laboratory An Automatic Methodology for Program Segment-based Compiler Optimization Search

Guang R. Gao, G. Gao, Xiaoming Li, 2022 .

ASAFESSS: A Scheduler-driven Adaptive Framework for Extreme Scale Software Stacks

Benoît Meister, Guang R. Gao, Tom St. John, 2014, ADAPT '14.