SPIRAL: Code Generation for DSP Transforms
Carnegie Mellon University · Drexel University · +3 more institutions
Abstract
Fast changing, increasingly complex, and diverse computing platforms pose central problems in scientific computing: How to achieve, with reasonable effort, portable optimal performance? We present SPIRAL, which considers this problem for the performance-critical domain of linear digital signal processing (DSP) transforms. For a specified transform, SPIRAL automatically generates high-performance code that is tuned to the given platform. SPIRAL formulates the tuning as an optimization problem and exploits the domain-specific mathematical structure of transform algorithms to implement a feedback-driven optimizer. Similar to a human expert, for a specified transform, SPIRAL "intelligently" generates and explores…
Citation impact
- FWCI
- 47.01
- Percentile
- 100%
- References
- 99
Authors
13Topics & keywords
- Computer science
- Digital signal processing
- Program optimization
- Code (set theory)
- Spiral (railway)
- Discrete Fourier transform (general)
- Algorithm
- Exploit