1 citations · 1 across the 3 of their papers we have counts for
3 papers
AMULET: Adaptive Matrix-Multiplication-Like Tasks
Junyoung Kim, Kenneth Ross, Eric Sedlar +1
Many useful tasks in data science and machine learning applications can be written as simple variations of matrix multiplication. However, users have difficulty performing such tas…
Control Flow Duplication for Columnar Arrays in a Dynamic Compiler
Sebastian Kloibhofer, Lukas Makor, David Leopoldseder +3
Columnar databases are an established way to speed up online analytical processing (OLAP) queries. Nowadays, data processing (e.g., storage, visualization, and analytics) is often…
Compilation Forking: A Fast and Flexible Way of Generating Data for Compiler-Internal Machine Learning Tasks
Raphael Mosaner, David Leopoldseder, Wolfgang Kisling +2
Compiler optimization decisions are often based on hand-crafted heuristics centered around a few established benchmark suites. Alternatively, they can be learned from feature and p…