Y
Yevgen Voronenko
Researcher at Carnegie Mellon University
Publications - 23
Citations - 1948
Yevgen Voronenko is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Fast Fourier transform & Discrete Fourier transform. The author has an hindex of 15, co-authored 21 publications receiving 1859 citations.
Papers
More filters
Journal ArticleDOI
SPIRAL: Code Generation for DSP Transforms
Markus Püschel,Jose M. F. Moura,Jeremy Johnson,David Padua,Manuela Veloso,Bryan Singer,Jianxin Xiong,Franz Franchetti,A. Gacic,Yevgen Voronenko,K. Chen,R. W. Johnson,Nick Rizzolo +12 more
TL;DR: SPIRAL generates high-performance code for a broad set of DSP transforms, including the discrete Fourier transform, other trigonometric transforms, filter transforms, and discrete wavelet transforms.
Journal ArticleDOI
Multiplierless multiple constant multiplication
Yevgen Voronenko,Markus Püschel +1 more
TL;DR: This work proposes a new algorithm for the multiple constant multiplication problem, which produces solutions that require up to 20% less additions and subtractions than the best previously known algorithm and can handle problem sizes as large as 100 32-bit constants in a time acceptable for most applications.
Journal ArticleDOI
Algebraic Signal Processing Theory: Cooley–Tukey Type Algorithms for DCTs and DSTs
Yevgen Voronenko,Markus Püschel +1 more
TL;DR: This paper systematically derive a large class of fast general-radix algorithms for various types of real discrete Fourier transforms (real DFTs) including the discrete Hartley transform (DHT) based on the algebraic signal processing theory.
Journal ArticleDOI
Discrete fourier transform on multicore
TL;DR: This article gives an overview on the techniques needed to implement the discrete Fourier transform (DFT) efficiently on current multicore systems and shows and analyzes DFT benchmarks of the fastest libraries available for the considered platforms.
Proceedings ArticleDOI
FFT program generation for shared memory: SMP and multicore
TL;DR: This work presents a shared memory extension of Spiral that consists of a rewriting system that manipulates the structure of transform algorithms to achieve load balancing and avoids false sharing, and of a backend to generate multithreaded code.