Sökning: "PolyBench"

Hittade 4 uppsatser innehållade ordet PolyBench.

1. 1. Benchmarking linear-algebra algorithms on CPU- and FPGA-based platforms

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Omar Askar Vergara; Karl Törnblom Bartholf; [2023]
   Nyckelord :FPGA; OpenCL; PolyBench; Cholesky; Durbin;

   Sammanfattning : Moore’s law is the main driving factor behind the rapid evolution of computers that has been observed in the past 50 years. Though the law is soon ending due to heat- and sizing-related issues. One solution to continuing the evolution is utilizing alternative computer hardware, where parallel hardware is especially interesting. LÄS MER

3. 2. A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

   Master-uppsats, Linköpings universitet/Programvara och system

   Författare :Erik Tedhamre; [2022]
   Nyckelord :;

   Sammanfattning : With hardware performance no longer following Moore’s law, software optimization becomes more important. In this paper, we discuss parallel programming, which is one way to optimize software. However, writing parallel code is considered more difficult than writing sequential code. LÄS MER

4. 3. Improving performance of sequential code through automatic parallelization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Claudius Sundlöf; [2018]
   Nyckelord :Automatic parallelization; benchmark; PolyBench; NPB; ICC; Cetus; autoPar; TC Optimizing Compiler; PLUTO;

   Sammanfattning : Automatic parallelization is the conversion of sequential code into multi-threaded code with little or no supervision. An ideal implementation of automatic parallelization would allow programmers to fully utilize available hardware resources to deliver optimal performance when writing code. LÄS MER

5. 4. Graph-based features for machine learning driven code optimization

   Master-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

   Författare :Anton Kindestam; [2017]
   Nyckelord :Machine Learning; Graph Kernel; Compilation; Big Data Tuning;

   Sammanfattning : In this paper we present a method of using the Shortest-Path Graph Kernel, on graph-based features of computer programs, to train a Support Vector Regression model which predicts execution time speedup over baseline given an unseen program and a point in optimization space, based on a method proposed in Using Graph-Based Program Characterization for Predictive Modeling by Park et al. The optimization space is represented by command-line parameters to the polyhedral C-to-C compiler PoCC, and PolyBench is used to generate the data set of speedups over baseline. LÄS MER