The popularity of Convolutional Neural Network (CNN) models and the ubiquity of CPUs
imply that better performance of CNN model inference on CPUs can deliver significant gain …

Register allocation (mapping variables to processor registers or memory) and instruction
scheduling (reordering instructions to increase instruction-level parallelism) are essential …

We show that register allocation can be viewed as solving a collection of puzzles. We model
the register file as a puzzle board and the program variables as puzzle pieces; pre-coloring …

Deep Neural Networks (DNNs) require very large amounts of computation, and many
different algorithms have been proposed to implement their most expensive layers, each of …

We aim to automate decades of research and experience in register allocation, leveraging
machine learning. We tackle this problem by embedding a multi-agent reinforcement …

Irregularly structured registers are hard to abstract and allocate. Partitioned Boolean
quadratic programming (PBQP) is a useful abstraction to represent complex register …

Instruction selection is a well-studied compiler phase that translates the compiler's
intermediate representation of programs to a sequence of target-dependent machine …

MOPED (MObile grouPEd Device) is a network model that treats a user's set of personal
devices as a single, virtual device. The nodes of the MOPED dynamically aggregate …

A graph-coloring register allocator that optimally allocates registers for structured programs
in polynomial time is presented. It can handle register aliasing. The assignment of registers …

The interaction of register allocation and instruction scheduling is a well-studied problem:
Certain ways of arranging instructions within basic blocks reduce overlaps of live ranges …