nVidia GeForce RTX 2070

hgpu.org » nVidia GeForce RTX 2070

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Fabian Knorr, Peter Thoman, Thomas Fahringer

View

Download (PDF)

Source codes

Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, Package, SYCL, Tesla V100

August 8, 2021 by hgpu

Lettuce: PyTorch-based Lattice Boltzmann Framework

Mario Christopher Bedrunka, Dominik Wilde, Martin Kliemank, Dirk Reith, Holger Foysi, Andreas Krämer

View

Download (PDF)

Source codes

Tags: Algorithms, Computational Physics, CUDA, Deep learning, Fluid dynamics, Lattice Boltzmann model, Machine learning, nVidia, nVidia GeForce RTX 2070, Package, Physics, Tesla V100

June 27, 2021 by hgpu

Early Experiences Migrating CUDA codes to oneAPI

Manuel Costanzo, Enzo Rucci, Carlos García Sanchez, Marcelo Naiouf

View

Download (PDF)

Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2070, Portability, SYCL

June 6, 2021 by hgpu

Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach

Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2070, Performance, Python, Tesla P100, Tesla V100

February 7, 2021 by hgpu

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Orestis Zachariadis, Nitin Satpute, Juan Gómez-Luna, Joaquín Olivares

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Matrix multiplication, Mixed precision, nVidia, nVidia GeForce RTX 2070, nVidia Titan RTX, Package, Performance, Sparse matrix

October 4, 2020 by hgpu

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Niclas Hedam, Jakob Mollerup, Pinar Tozun

View

Download (PDF)

Tags: Computer science, CUDA, Databases, Hashing, nVidia, nVidia GeForce RTX 2070, OpenCL, Security, Tesla V100

September 6, 2020 by hgpu

Heterogeneous parallel computing for image registration and linear algebra applications

Orestis Zachariadis

View

Download (PDF)

Source codes

Tags: CUDA, Heterogeneous systems, Image processing, Image registration, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2070, Package, Sparse matrix, Thesis

August 9, 2020 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

View

Download (PDF)

Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 by hgpu

ComScribe: a tool that identifies communication among all GPU-GPU and CPU-GPU pairs in a single-node multi-GPU system

Monitoring Collective Communication Among GPUs

HLS Portability from Intel to Xilinx: A Case Study

HEXL: Intel Homomorphic Encryption Acceleration Library

Accelerating Encrypted Computing on Intel GPUs

Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

CompilerGym: a library performant reinforcement learning environments for compiler tasks

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Lettuce: PyTorch-based Lattice Boltzmann Framework

Early Experiences Migrating CUDA codes to oneAPI

Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Heterogeneous parallel computing for image registration and linear algebra applications

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Recent source codes

ComScribe: a tool that identifies communication among all GPU-GPU and CPU-GPU pairs in a single-node multi-GPU system

PHCpack

HEVolRender: Homomorphic-Encrypted Volume Rendering

Vina-GPU: A heterogeneous OpenCL implementation of AutoDock Vina

GCN Inference Acceleration HLS

Climate Machine: an Earth System Model that automatically learns from data

HLS Portability from Intel to Xilinx: A Case Study

HEXL: Intel Homomorphic Encryption Acceleration Library

Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System

CompilerGym: a library performant reinforcement learning environments for compiler tasks

Most viewed papers (last 30 days)