high performance computing on graphics processing units: hgpu.org

hgpu.org » Intel Xeon Phi

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Mohammed A. Noaman Al-hayanni, Rishad Shafik, Ashur Rafiev, Fei Xia, Alex Yakovlev

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

June 5, 2017 by hgpu

A performance spectrum for parallel computational frameworks that solve PDEs

J. Chang, K. B. Nakshatrala, M. G. Knepley, L. Johnsson

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Tags: Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, MPI, Partial differential equations, PDEs

June 1, 2017 by hgpu

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Michal Merta, Lubomir Riha, Ondrej Meca, Alexandros Markopoulos, Tomas Brzobohaty, Tomas Kozubek, Vit Vondrak

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Tags: Algorithms, Computer science, Intel Xeon Phi, Laplace and Poisson equation, OpenMP, Package, Sparse direct solvers, Sparse matrix

May 24, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 by hgpu

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

Berenger Bramas

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Sorting

May 9, 2017 by hgpu

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Bin Chen, Ronald Kantowski, Xinyu Dai, Eddie Baron, Paul Van der Mark

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Tags: Astrophysics, CUDA, Gravitation, Gravitational lensing, Intel Xeon Phi, nVidia, OpenMP, Tesla M2050

May 2, 2017 by hgpu

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Peter Labus

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Tags: Algorithms, HEP, Heterogeneous systems, Intel Xeon Phi, OpenMP, Physics, QCD, Thesis

April 26, 2017 by hgpu

Capability Models for Manycore Memory Systems: A Case-Study with Xeon Phi KNL

Sabela Ramos, Torsten Hoefler

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Tags: Computer science, Intel Xeon Phi, Memory, MPI, OpenMP

April 20, 2017 by hgpu

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

Suejb Memeti, Lu Li, Sabri Pllana, Joanna Kolodziej, Christoph Kessler

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Performance

April 20, 2017 by hgpu

Parallelized Kendall’s Tau Coefficient Computation via SIMD Vectorized Sorting On Many-Integrated-Core Processors

Yongchao Liu, Tony Pan, Oded Green, Srinivas Aluru

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Tags: Algorithms, Computer science, Distributed computing, Intel Xeon Phi, MPI, Package, Sorting

April 15, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

Vectorization of Hybrid Breadth First Search on the Intel Xeon Phi

Mireya Paredes, Graham Riley, Mikel Lujan

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Parallelization

April 11, 2017 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

A performance spectrum for parallel computational frameworks that solve PDEs

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Fast Sorting Algorithms using AVX-512 on Intel Knights Landing

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Capability Models for Manycore Memory Systems: A Case-Study with Xeon Phi KNL

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

Parallelized Kendall’s Tau Coefficient Computation via SIMD Vectorized Sorting On Many-Integrated-Core Processors

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Vectorization of Hybrid Breadth First Search on the Intel Xeon Phi

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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