Automatic vectorization is an important technique for compilers to improve the parallelism of
programs. With the widespread usage of SIMD (Single Instruction Multiple Data) extensions …

This paper advocates programming high-performance code using partial evaluation. We
present a clean-slate programming system with a simple, annotation-based, online partial …

Partial control-flow linearization is a code transformation conceived to maximize work
performed in vectorized programs. In this article, we find a new service for it. We show that …

Superword-level parallelism (SLP) vectorization is a proven technique for vectorizing
straight-line code. It works by replacing independent, isomorphic instructions with equivalent …

Loop unrolling is a widely adopted loop transformation, commonly used for enabling
subsequent optimizations. Straight-line-code vectorization (SLP) is an optimization that …

GPGPUs use the Single-Instruction-Multiple-Thread (SIMT) execution model where a group
of threads—wavefront or warp—execute instructions in lockstep. When threads in a group …

Attacks exploiting speculative execution, known as Spectre attacks, have gained substantial
attention in the scientific community and in industry with a broad range of defense …

SLP Auto-vectorization converts straight-line code into vector code. It scans input code for
groups of instructions that can be combined into vectors and replaces them with their …

A program is said to be isochronous if its running time does not depend on classified
information. The programming languages literature contains much work that transforms …

A modern GPU is designed with many large thread groups to achieve a high throughput and
performance. Within these groups, the threads are grouped into fixed-size SIMD batches in …