49 citations · 109 across the 8 of their papers we have counts for
8 papers
A variational study of two-nucleon systems with lattice QCD
Saman Amarasinghe, Riyadh Baghdadi, Zohreh Davoudi +6
The low-energy spectrum and scattering of two-nucleon systems are studied with lattice quantum chromodynamics using a variational approach. A wide range of interpolating operators…
A Deep Learning Based Cost Model for Automatic Code Optimization
Riyadh Baghdadi, Massinissa Merouani, Mohamed-Hicham Leghettas +4
Enabling compilers to automatically optimize code has been a longstanding goal for the compiler community. Efficiently solving this problem requires using precise cost models. Thes…
TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning
Riyadh Baghdadi, Abdelkader Nadir Debbagh, Kamel Abdous +5
In this paper, we demonstrate a compiler that can optimize sparse and recurrent neural networks, both of which are currently outside of the scope of existing neural network compile…
GraphIt: A High-Performance DSL for Graph Analytics
Yunming Zhang, Mengjiao Yang, Riyadh Baghdadi +3
The performance bottlenecks of graph applications depend not only on the algorithm and the underlying hardware, but also on the size and structure of the input graph. Programmers m…
Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code
Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane +6
This paper introduces Tiramisu, a polyhedral framework designed to generate high performance code for multiple platforms including multicores, GPUs, and distributed machines. Tiram…
Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers
Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane +4
High-performance DSL developers work hard to take advantage of modern hardware. The DSL compilers have to build their own complex middle-ends before they can target a common back-e…