A practical automatic polyhedral parallelizer and locality optimizer

U Bondhugula, A Hartono, J Ramanujam… - Proceedings of the 29th …, 2008‏ - dl.acm.org
We present the design and implementation of an automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …

Automatic transformations for communication-minimized parallelization and locality optimization in the polyhedral model

U Bondhugula, M Baskaran, S Krishnamoorthy… - … CC 2008, Held as Part of …, 2008‏ - Springer
The polyhedral model provides powerful abstractions to optimize loop nests with regular
accesses. Affine transformations in this model capture a complex sequence of execution …

[PDF][PDF] Pluto: A practical and fully automatic polyhedral program optimization system

U Bondhugula, A Hartono, J Ramanujam… - Proceedings of the …, 2008‏ - researchgate.net
We present the design and implementation of a fully automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …

Automatic C-to-CUDA code generation for affine programs

MM Baskaran, J Ramanujam… - … , CC 2010, Held as Part of …, 2010‏ - Springer
Abstract Graphics Processing Units (GPUs) offer tremendous computational power. CUDA
(Compute Unified Device Architecture) provides a multi-threaded parallel programming …

Domain-specific multi-level ir rewriting for gpu: The open earth compiler for gpu-accelerated climate simulation

T Gysi, C Müller, O Zinenko, S Herhut, E Davis… - ACM Transactions on …, 2021‏ - dl.acm.org
Most compilers have a single core intermediate representation (IR)(eg, LLVM) sometimes
complemented with vaguely defined IR-like data structures. This IR is commonly low-level …

Polyhedral specification and code generation of sparse tensor contraction with co-iteration

T Zhao, T Popoola, M Hall, C Olschanowsky… - ACM Transactions on …, 2022‏ - dl.acm.org
This article presents a code generator for sparse tensor contraction computations. It
leverages a mathematical representation of loop nest computations in the sparse polyhedral …

Graphite two years after: First lessons learned from real-world polyhedral compilation

K Trifunovic, A Cohen, D Edelsohn, F Li… - … Workshop (GROW'10 …, 2010‏ - inria.hal.science
Modern compilers are responsible for adapting the semantics of source programs into a form
that makes efficient use of a highly complex, heterogeneous machine. This adaptation …

Automatic data movement and computation map** for multi-level parallel architectures with explicitly managed memories

MM Baskaran, U Bondhugula… - Proceedings of the 13th …, 2008‏ - dl.acm.org
Several parallel architectures such as GPUs and the Cell processor have fast explicitly
managed on-chip memories, in addition to slow off-chip memory. They also have very high …

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

M Merouani, KA Boudaoud, IN Aouadj… - arxiv preprint arxiv …, 2024‏ - arxiv.org
While polyhedral compilers have shown success in implementing advanced code
transformations, they still have challenges in selecting the most profitable transformations …

Compiler-assisted dynamic scheduling for effective parallelization of loop nests on multicore processors

MM Baskaran, N Vydyanathan, UKR Bondhugula… - ACM sigplan …, 2009‏ - dl.acm.org
Recent advances in polyhedral compilation technology have made it feasible to
automatically transform affine sequential loop nests for tiled parallel execution on multi-core …