Tuning compiler optimizations for rapidly evolving hardware makes porting and extending
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …

Heterogeneous architectures are currently widespread. With the advent of easy-to-program
general purpose GPUs, virtually every recent desktop computer is a heterogeneous system …

We present Astra, a compilation and execution framework that optimizes execution of a deep
learning training job. Instead of treating the computation as a generic data flow graph, Astra …

Determining the best set of optimizations to apply to a program has been a long standing
problem for compiler writers. To reduce the complexity of this task, existing approaches …

Iterative compilation techniques, which involve iterating over different sets of optimizations,
have proven useful in helping compilers choose the right set of optimizations for a given …

Coping with software defects that occur in the post-deployment stage is a challenging
problem: bugs may occur only when the system uses a specific configuration and only under …

Memory bloat is an important source of inefficiency in complex production software,
especially in software written in managed languages such as Java. Prior approaches to this …

Iterative optimization is a popular and efficient research approach to optimize programs
using feedback-directed compilation. However, one of the key limitations that prevented …

Support Vector Machines (SVMs) are used to discover method-specific compilation
strategies in Testarossa, a commercial Just-in-Time (JiT) compiler employed in the IBM® J9 …

This paper presents a finding and a technique on program behavior prediction. The finding
is that surprisingly strong statistical correlations exist among the behaviors of different …