NVIDIA Research Projects

Login: NVlabs

Company: null

Location: null

email:

Blog: http://research.nvidia.com

Members

  1. Nuno Subtil

Repositories

AdaBatch
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
cub
CUB is a flexible library of cooperative threadblock primitives and other utilities for CUDA kernel programming.
dlinputs
Input pipelines for large scale, sharded training of deep learning models.
dlmodels
Size inference and pipeline notation for PyTorch models.
dltrainers
Utility functions for training PyTorch models.
fermat
Fermat is a high performance research oriented physically based rendering system, trying to produce beautiful pictures following the mathematician?s principle of least time
firepony
Efficient base quality score recalibrator for NGS data
GA3C
Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.
geomapnet
Geometry-Aware Learning of Maps for Camera Localization (CVPR2018)
litmustestgen
Alloy models for automatic synthesis of memory model litmus test suites (from ASPLOS 2017)
MUNIT
null
nvbio
NVBIO is a library of reusable components designed to accelerate bioinformatics applications using CUDA.
nvbio-gpl
NVBIO is a library of reusable components designed to accelerate bioinformatics applications using CUDA.
ocrobin
null
ocrodeg
document image degradation
ocroline
null
ocropus3
Repository collecting all the submodules for the new PyTorch-based OCR System.
ocrorot
Rotation and skew detection using DL.
ocroseg
null
PL4NN
Perceptual Losses for Neural Networks: Caffe implementation of loss layers based on perceptual image quality metrics.
rdir
RDIR Compiler Plug-in
SASSI
Flexible GPGPU instrumentation
sassifi
An Architecture-level Fault Injection Tool for GPU Application Resilience Evaluations
xmp
CUDA accelerated(X) Multi-Precision library
This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.