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This is the home page of the SPIRAL project. The goal of SPIRAL is to push the limits of automation in software and hardware development and optimization for digital signal processing (DSP) algorithms and other numerical kernels beyond what is possible with current tools.

Our basic research question is

Can we teach computers to write fast libraries?

Our flagship is the SPIRAL program generation system, which, entirely autonomously, generates platform-tuned implementations of signal processing transform such as the discrete Fourier transform, discrete cosine transform, and many others. Look at a few benchmarks. But we also provide other online generators (see the right column).

SPIRAL addresses one of the current key problems in numerical software and hardware development: how to achieve close to optimal performance with reasonable coding effort? (More detailed problem statement.)

SPIRAL comprises an interdisciplinary team of researchers in the areas of signal processing, algorithms, scientific computing, compilers, computer architecture, and mathematics.

In the domain of linear transform, and for standard multicore platforms (Core 2 Duo like), we have achieved complete automation: the computer generation of general input-size, vectorized, parallel libraries.

Ongoing Research

PAL (Pareto Active Learning) Algorithm for Multi-objective Optimization
Optimized sparse FFT
Generate code for Intel IPP 6.0, which now has an entire domain for Spiral-generated code
DFT code generation for the Cell BE
DFT IP generation for FPGAs
Software generation for Viterbi decoding
Multi-gigabit optical OFDM

Learn Quickly About Spiral

This short article in the recent Encyclopedia of Parallel Computing describes the main ideas behind our program synthesis work for transforms:

Markus Püschel, Franz Franchetti and Yevgen Voronenko
Spiral
in Encyclopedia of Parallel Computing, Eds. David Padua, Springer 2011

Good Choice for Citing Spiral (Early Overview Paper)

Markus Püschel, José M. F. Moura, Jeremy Johnson, David Padua, Manuela Veloso, Bryan Singer, Jianxin Xiong, Franz Franchetti, Aca Gacic, Yevgen Voronenko, Kang Chen, Robert W. Johnson, and Nick Rizzolo
SPIRAL: Code Generation for DSP Transforms
Proceedings of the IEEE special issue on "Program Generation, Optimization, and Adaptation," Vol. 93, No. 2, 2005, pp. 232-275

After this paper we started to attack all forms of parallel platforms. Check out benchmarks or learn about the current Spiral system.

Online Generators

We provide a number of online generators, which are easy and fun to use or play with.

Online generators currently available

Software (C code)

Hardware (Verilog)

Linear transforms
(DFT, DCT, many others)

Multiplierless multiplication

Multiplierless filters

DFT = discrete Fourier transform, DCT = discrete cosine transform.

Browse other software and hardware.

Contact

If you have questions or comments about SPIRAL or our work in general, please send email to help (at) spiral.net.

SPIRAL Team

NSF Discovery

July 2008: Computer generation of libraries using Spiral was selected as NSF discovery.

Thesis Award

May 2008: Yevgen Voronenko receives the ECE/CMU best thesis award. With the thesis the computer generation of high performance transform libraries becomes possible.

Intel Collaboration

April 2008: Intel announces that its flagship performance library IPP (6.0 beta) will have a domain for library functions generated by Spiral.

Beyond Transforms

Our strength are transforms. But we study program generation for various problems:

Tools

Funding

In 2007/2008 we received grants from Darpa, NSF, Intel, Mercury, and National Instruments.

Proceedings IEEE Special Issue

Program Generation, Optimization, and Adaptation

How to Cite SPIRAL

If you consider citing SPIRAL, here is our suggestion.