Browsing Computer Science and Automation (CSA) by Advisor "Bondhugula, Uday"
Now showing items 1-7 of 7
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Automatic Data Allocation, Buffer Management And Data Movement For Multi-GPU Machines
(2017-05-24)Multi-GPU machines are being increasingly used in high performance computing. These machines are being used both as standalone work stations to run computations on medium to large data sizes (tens of gigabytes) and as a ... -
Automatic Storage Optimization of Arrays Affine Loop Nests
(2018-03-01)Efficient memory usage is crucial for data-intensive applications as a smaller memory footprint ensures better cache performance and allows one to run a larger problem size given a axed amount of main memory. The solutions ... -
Effective Automatic Computation Placement and Data Allocation for Parallelization of Regular Programs
(2018-02-15)Scientific applications that operate on large data sets require huge amount of computation power and memory. These applications are typically run on High Performance Computing (HPC) systems that consist of multiple compute ... -
An MLIR-Based High-Level Synthesis Compiler for Hardware Accelerator Design
The emergence of machine learning, image and audio processing on edge devices has motivated research towards power-efficient custom hardware accelerators. Though FPGAs are an ideal target for custom accelerators, the ... -
An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations
(2018-03-09)Lattice-Boltzmann method(LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a ... -
Polymage : Automatic Optimization for Image Processing Pipelines
(2018-06-25)Image processing pipelines are ubiquitous. Every image captured by a camera and every image uploaded on social networks like Google+or Facebook is processed by a pipeline. Applications in a wide range of domains like ... -
Tiling Stencil Computations To Maximize Parallelism
(2017-05-21)Stencil computations are iterative kernels often used to simulate the change in a discretized spatial domain overtime (e.g., computational fluid dynamics) or to solve for unknowns in a discretized space by converging to a ...