VLDB 2026 Research / reviewers in the wild / expert
Luning Cao
dblp:252/4630
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization
code generation |
0.4 | 1 | 2019 | 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 |
0.4 | 1 | 2019 | AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019 |
High-performance computing
performance optimization |
0.4 | 1 | 2019 | 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 |
0.1 | 1 | 2019 | AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs · SC 2019 |
High-performance computing › scientific computing
scientific computing kernels |
0.1 | 1 | 2019 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUsabstractThe 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 |
SC | 6 |