Parameterized micro-benchmarking
Wenjing Ma, Sriram Krishnamoorthy, Gagan Agrawal · 2012
Auto-tuning has emerged as an important practical method for creating highly optimized implementations of key computational kernels and applications. However, the growing complexity of architectures and applications is creating new challenges for auto-tuning. Complex applications can involve a prohibitively large search space that precludes empirical auto-tuning. Similarly, architectures are getting more complicated, making it hard to model performance.