Since the mid-1990s, researchers have been trying to use machine-learning-based
approaches to solve a number of different compiler optimization problems. These …

Modern microprocessors can achieve high performance on linear algebra kernels but this
currently requires extensive machinoapeci6c hand tuning. We have developed a …

It is often impossible to obtain a one-size-fits-all solution for high performance algorithms
when considering different choices for data distributions, parallelism, transformations, and …

Virtually all real-valued computations are carried out using floating-point data types and
operations. The precision of these data types must be set with the goals of reducing the …

This dissertation presents an automated system to generate highly efficient, platform-
adapted implementations of sparse matrix kernels. We show that conventional …

Applying the right compiler optimizations to a particular program can have a significant
impact on program performance. Due to the non-linear interaction of compiler optimizations …

High-level program optimizations, such as loop transformations, are critical for high
performance on multi-core targets. However, complex sequences of loop transformations …

Tuning large applications requires a clever exploration of the design and configuration
space. Especially on supercomputers, this space is so large that its exhaustive traversal via …

Finite-precision arithmetic, widely used in embedded systems for numerical calculations,
faces an inherent tradeoff between accuracy and efficiency. The points in this tradeoff space …

The excessive complexity of both machine architectures and applications have made it
difficult for compilers to statically model and predict application behavior. This observation …