Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

04/27/2018
by   Riyadh Baghdadi, et al.
0

This paper introduces Tiramisu, a polyhedral framework designed to generate high performance code for multiple platforms including multicores, GPUs, and distributed machines. Tiramisu introduces a scheduling language with novel extensions to explicitly manage the complexities that arise when targeting these systems. The framework is designed for the areas of image processing, stencils, linear algebra and deep learning. Tiramisu has two main features: it relies on a flexible representation based on the polyhedral model and it has a rich scheduling language allowing fine-grained control of optimizations. Tiramisu uses a four-level intermediate representation that allows full separation between the algorithms, loop transformations, data layouts, and communication. This separation simplifies targeting multiple hardware architectures with the same algorithm. We evaluate Tiramisu by writing a set of image processing, deep learning, and linear algebra benchmarks and compare them with state-of-the-art compilers and hand-tuned libraries. We show that Tiramisu matches or outperforms existing compilers and libraries on different hardware architectures, including multicore CPUs, GPUs, and distributed machines.

READ FULL TEXT
research
04/27/2018

Tiramisu: A Code Optimization Framework for High Performance Systems

This paper introduces Tiramisu, an optimization framework designed to ge...
research
11/10/2019

Using Deep Neural Networks for Estimating Loop Unrolling Factor

Optimizing programs requires deep expertise. On one hand, it is a tediou...
research
02/28/2018

Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers

High-performance DSL developers work hard to take advantage of modern ha...
research
03/15/2022

DISTAL: The Distributed Tensor Algebra Compiler

We introduce DISTAL, a compiler for dense tensor algebra that targets mo...
research
11/21/2019

The Linear Algebra Mapping Problem

We observe a disconnect between the developers and the end users of line...
research
08/01/2023

Leveraging MLIR for Loop Vectorization and GPU Porting of FFT Libraries

FFTc is a Domain-Specific Language (DSL) for designing and generating Fa...
research
12/22/2022

A Domain-Extensible Compiler with Controllable Automation of Optimisations

In high performance domains like image processing, physics simulation or...

Please sign up or login with your details

Forgot password? Click here to reset