Moving data through the memory hierarchy is a fundamental bottleneck that can limit the
performance of core algorithms of machine learning, such as convolutional neural networks …

In this paper, we present constrained simulated annealing (CSA), an algorithm that extends
conventional simulated annealing to look for constrained local minima of nonlinear …

Empirical optimizers like ATLAS have been very effective in optimizing computational
kernels in libraries. The best choice of parameters such as tile size and degree of loop …

We present a system for the automatic synthesis of efficient algorithms specialized for a
particular memory hierarchy and a set of storage devices. The developer provides two …

Compile‐time optimizations involve a number of transformations such as loop permutation,
fusion, tiling, array contraction etc. The selection of the appropriate transformation to …

(1) where z=(x, y) T∈ Z; x∈ Rv and y∈ Dw are, respectively, bounded continuous and
discrete variables; f (z) is a lower-bounded objective function; g (z)=(g1 (z),…, gr (z)) T is a …

Compile-time optimizations involve a number of transformations such as loop permutation,
fusion, tiling, array contraction, etc. Determination of the choice of these transformations that …

Abstract The Global Arrays (GA) toolkit provides a shared-memory programming model in
which data locality is explicitly managed by the programmer. It inter-operates with MPI and …

This dissertation describes the implementation of the mathematical expressiveness in the
Diderot programming language. Diderot is a domain-specific language for scientific …

Diderot is a parallel domain-specific language for analysis and visualization of
multidimensional scientific images, such as those produced by CT and MRI scanners. In …