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A practical automatic polyhedral parallelizer and locality optimizer
We present the design and implementation of an automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …
transformation framework that can optimize regular programs (sequences of possibly …
Automatic transformations for communication-minimized parallelization and locality optimization in the polyhedral model
The polyhedral model provides powerful abstractions to optimize loop nests with regular
accesses. Affine transformations in this model capture a complex sequence of execution …
accesses. Affine transformations in this model capture a complex sequence of execution …
[PDF][PDF] Pluto: A practical and fully automatic polyhedral program optimization system
We present the design and implementation of a fully automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …
transformation framework that can optimize regular programs (sequences of possibly …
Automatic C-to-CUDA code generation for affine programs
Abstract Graphics Processing Units (GPUs) offer tremendous computational power. CUDA
(Compute Unified Device Architecture) provides a multi-threaded parallel programming …
(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
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 …
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
This article presents a code generator for sparse tensor contraction computations. It
leverages a mathematical representation of loop nest computations in the sparse polyhedral …
leverages a mathematical representation of loop nest computations in the sparse polyhedral …
Graphite two years after: First lessons learned from real-world polyhedral compilation
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 …
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
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 …
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
While polyhedral compilers have shown success in implementing advanced code
transformations, they still have challenges in selecting the most profitable transformations …
transformations, they still have challenges in selecting the most profitable transformations …
Compiler-assisted dynamic scheduling for effective parallelization of loop nests on multicore processors
Recent advances in polyhedral compilation technology have made it feasible to
automatically transform affine sequential loop nests for tiled parallel execution on multi-core …
automatically transform affine sequential loop nests for tiled parallel execution on multi-core …