Heterogeneous systems | Page 32

hgpu.org » Heterogeneous systems

Task Scheduling for Heterogeneous Multicore Systems

Zhuo Chen, Diana Marculescu

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 760 Ti, OpenCL, Task scheduling

December 15, 2017 by hgpu

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Jose Marques, Gabriel Falcao, Luis A. Alexandre

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7500 M, CNN, Computer science, CUDA, Deep learning, Heterogeneous systems, Matlab, Neural networks, nVidia, nVidia GeForce GTX 840 M, nVidia GeForce GTX 940 M, nVidia GeForce GTX 950 M, OpenCL, Tesla K20

December 10, 2017 by hgpu

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Marcio M. Pereira, Rafael C. F. Sousa, Guido Araujo

View

Download (PDF)

Source codes

Tags: ARM, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, LLVM, nVidia, OpenCL, OpenMP, Package, Tesla K40

November 21, 2017 by hgpu

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Allen Rush, Ashish Sirasao, Mike Ignatowski

View

Download (PDF)

Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Machine learning, OpenCL

November 21, 2017 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

View

Download (PDF)

Source codes

Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David Kaeli, Qianqian Fang

View

Download (PDF)

Source codes

Tags: Algorithms, AMD R9 Nano, AMD Radeon RX 480, ATI, Computational Physics, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 590, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, OpenCL, Package, Physics

November 12, 2017 by hgpu

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Gaurav Mitra

View

Download (PDF)

Tags: ARM, Benchmarking, Computer science, DSP, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, OpenCL, SoC, Thesis

November 12, 2017 by hgpu

Data Coherence Analysis and Optimization for Heterogeneous Computing

Rafael Sousa, Marcio Pereira, Fernando Magno Quintao Pereira, Guido Araujo

View

Download (PDF)

Tags: ARM, Compilers, Computer science, Heterogeneous systems, OpenCL

November 5, 2017 by hgpu

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

Yong-Xian Wang, Li-Lun Zhang, Wei Liu, Xing-Hua Cheng, Yu Zhuang, Anthony T. Chronopoulos

View

Download (PDF)

Tags: cfd, Computer science, CUDA, Fluid dynamics, Heterogeneous systems, MPI, nVidia, OpenMP, Performance, supercomputer, Tesla M2050, Xeon Phi

October 31, 2017 by hgpu

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Jude-Thaddeus Ojiaku

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7750, ATI Radeon HD 7970, Bioinformatics, Computer science, Graph layout, Heterogeneous systems, nVidia, nVidia GefForce GTX 650, nVidia GefForce GTX 680, OpenCL, Thesis

October 29, 2017 by hgpu

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Tyler Fox

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, SoC, Thesis

October 21, 2017 by hgpu

Toward Performance Portability for CPUs and GPUs Through Algorithmic Compositions

Li-Wen Chang

View

Download (PDF)

Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, OpenCL, performance portability, Tesla C2050, Tesla K20, Thesis

October 15, 2017 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Task Scheduling for Heterogeneous Multicore Systems

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Data Coherence Analysis and Optimization for Heterogeneous Computing

Performance optimizations for scalable CFD applications on hybrid CPU+MIC heterogeneous computing system with millions of cores

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Revisiting the Case of ARM SoCs in High-Performance Computing Clusters

Toward Performance Portability for CPUs and GPUs Through Algorithmic Compositions

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Most viewed papers (last 30 days)