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Luning Cao

dblp:252/4630 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 50% Program synthesis and code generation · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 81% Hardware accelerators and domain-specific architectures · 19%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Compilers and program optimization
code generation
0.412019
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019
Program synthesis and code generation › generative programming
template-based code generation
0.412019
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019
High-performance computing
performance optimization
0.412019
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019
Hardware accelerators and domain-specific architectures
discrete fourier transform
0.112019
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019
High-performance computing › scientific computing
scientific computing kernels
0.112019
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019

Methods — techniques the papers use, named apart from their topics

cooley-tukey algorithm · 0.8assembly template optimization · 0.8
YearPublicationVenuePosition
2019 AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs
abstract
The discrete Fourier transform (DFT) is widely used in scientific and engineering computation. This paper proposes a template-based code generation framework named AutoFFT that can automatically generate high-performance fast Fourier transform (FFT) codes. AutoFFT employs the Cooley-Tukey FFT algorithm, which exploits the symmetric and periodic properties of the DFT matrix as the outer parallelization framework. To further reduce the number of floating-point operations of butterflies, we explore more symmetric and periodic properties of the DFT matrix and formulate two optimized calculation templates for prime and power-of-two radices. To fully exploit hardware resources, we encapsulate a series of optimizations in an assembly template optimizer. Given any DFT problem, AutoFFT automatically generates C FFT kernels using these two templates and transfers them to efficient assembly codes using the template optimizer. Experiments show that AutoFFT outperforms FFTW, ARMPL, and Intel MKL on average across all FFT types on ARMv8 and Intel x86-64 processors.
Zhihao Li 0001, Haipeng Jia, Yunquan Zhang, Tun Chen, Luning Cao
SC6