nVidia | Page 83 | hgpu.org

hgpu.org » nVidia

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Beau Johnston, Jeffrey S. Vetter, Josh Milthorpe

View

Download (PDF)

Source codes

Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, CUDA, Heterogeneous systems, HIP, Matrix multiplication, nVidia, OpenCL, Package, Performance, Tesla P100

November 29, 2020 by hgpu

Efficient Deep Neural Network Inference for Embedded Systems: A Mixture of Experts Approach

Benjamin David Taylor

View

Download (PDF)

Tags: Algorithms, Cloud, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia Jetson TX2, Thesis

November 29, 2020 by hgpu

HALO 1.0: A Hardware-agnostic Accelerator Orchestration Framework for Enabling Hardware-agnostic Programming with True Performance Portability for Heterogeneous HPC

Michael Riera, Erfan Bank Tavakoli, Masudul Hassan Quraishi, Fengbo Ren

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, HPC, MPI, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, performance portability

November 29, 2020 by hgpu

BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs

Massimo Bernaschi, Pasqua D'Ambra, Dario Pasquini

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, multigrid, nVidia, Package, Sparse linear iterative solver

November 29, 2020 by hgpu

AZP: Automatic Specialization for Zero Values in Gaming Applications

Mark W. Stephenson, Ram Rangan

View

Download (PDF)

Tags: Computer science, Games, HLSL, nVidia, nVidia GeForce RTX 2080, OpenGL, Performance, Vulkan

November 29, 2020 by hgpu

A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression

Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao

View

Download (PDF)

Source codes

Tags: Compression, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla V100

November 22, 2020 by hgpu

Ginkgo – A Math Library designed for Platform Portability

Terry Cojean, Yu-Hsiang "Mike" Tsai, Hartwig Anzt

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, HIP, nVidia, Package, Performance, performance portability

November 22, 2020 by hgpu

Adaptive Data Migration in Load-Imbalanced HPC Applications

Parsa Amini

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, HPC, load balancing, nVidia, Package, Tesla P100, Tesla V100, Thesis

November 15, 2020 by hgpu

Runtime Performances Benchmark for Knowledge Graph Embedding Methods

Angelica Sofia Valeriani

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 960, Package

November 15, 2020 by hgpu

Exploring the acceleration of Nekbone on reconfigurable architectures

Nick Brown

View

Download (PDF)

Tags: Computer science, FPGA, HLS, nVidia, OpenCL, Tesla V100

November 15, 2020 by hgpu

FastSVC: Fast Cross-Domain Singing Voice Conversion with Feature-wise Linear Modulation

Songxiang Liu, Yuewen Cao, Na Hu, Dan Su, Helen Meng

View

Download (PDF)

Tags: Computer science, nVidia, Speech recognition, Tesla P40

November 15, 2020 by hgpu

Automatic GPU optimization through higher-order functions in functional languages

John Wikman

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia Quadro P 2000, Optimization, Thesis

November 15, 2020 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Evaluating the Performance and Portability of Contemporary SYCL Implementations

HALO 1.0: A Hardware-agnostic Accelerator Orchestration Framework for Enabling Hardware-agnostic Programming with True Performance Portability for Heterogeneous HPC

BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs

AZP: Automatic Specialization for Zero Values in Gaming Applications

A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression

Ginkgo – A Math Library designed for Platform Portability

Adaptive Data Migration in Load-Imbalanced HPC Applications

Runtime Performances Benchmark for Knowledge Graph Embedding Methods

Exploring the acceleration of Nekbone on reconfigurable architectures

FastSVC: Fast Cross-Domain Singing Voice Conversion with Feature-wise Linear Modulation

Automatic GPU optimization through higher-order functions in functional languages

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

Most viewed papers (last 30 days)