Tags » GPGPU

Developing a Linux Kernel Module using GPUDirect RDMA

Taken from Developing a Linux Kernel Module using GPUDirect RDMA

1.0 Overview

GPUDirect RDMA is a technology introduced in Kepler-class GPUs and CUDA 5.0 that enables a direct path for data exchange between the GPU and a third-party peer device using standard features of PCI Express. 314 more words


GPGPU - Agent bodies facade

Investigations into agent bodies algorithms, and behavioral algorithms, where gradients and levels of differentiation are not predefined but rather a result of emergence.
#GPGPU #Stigmergy… 341 more words

My Project's

Hacking MIOpen to run anywhere and libre ML - lightingtalk@COSCUP 2017 Postscript

MIOpen. What a great library it is.

COSCUP 2017 just occurred last weekend. And I decided to attend to the lightning talk on how I get MIOpen to run on non AMD hardware and my vision on what this library could be. 371 more words


IBM touts improved distributed training time for visual recognition models

Two months ago, Facebook’s AI Research Lab (FAIR) published some impressive training times for massively distributed visual recognition models. Today IBM is firing back with some numbers of its own. 472 more words


Building AMD's MIOpen on a non ROCm(AMD) system

AMD. Please, please write your build script PROPERLY. It really sucks that I have to hack your code to make it work on other’s platform. – and that’s when all components used are cross platform. 556 more words


CUDA, Theano, and Antivirus

Most ubiquitous antivirus products monitor new process from executables in real time and will attempt to terminate their execution if deemed a potential threat. Some of these antivirus products simply do a signature match while some do more sophisticated heuristic or intelligent scanning. 421 more words


Microsoft’s high-performance, open source, deep learning toolkit is now generally available - Microsoft Cognitive Toolkit

Microsoft Cognitive Toolkit version 2.0 is now in full release with general availability. Cognitive Toolkit enables enterprise-ready, production-grade AI by allowing users to create, train, and evaluate their own neural networks that can then scale efficiently across multiple GPUs and multiple machines on massive data sets. 32 more words