GTC ON-DEMAND

 
SEARCH SESSIONS
SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Presentation
Media
Abstract:
Loading and storing file content to remote disk in CUDA applications typically requires using traditional file and network abstractions provided by the operating system. We'll show how GPUDirect changes that, making it possible to expose GPU memory directly to third-party devices such as NVM Express (NVMe). We'll introduce our proof-of-concept software library for creating GPU-Oriented storage applications with GPUDirect-capable GPUs and commodity NVMe disks residing in multiple remote hosts. Learn how we use the memory-mapping capabilities of PCIe non-transparent bridges to set up efficient I/O data paths between GPUs and disks that are attached to different root complexes (hosts) in a PCIe network. We'll demonstrate how our solution can initiate remote disk I/O from within a CUDA kernel. We will also compare our approach to state-of-the-art NVMe over fabrics and share our results for running a distributed workload on multiple GPUs using a remote disk.
Loading and storing file content to remote disk in CUDA applications typically requires using traditional file and network abstractions provided by the operating system. We'll show how GPUDirect changes that, making it possible to expose GPU memory directly to third-party devices such as NVM Express (NVMe). We'll introduce our proof-of-concept software library for creating GPU-Oriented storage applications with GPUDirect-capable GPUs and commodity NVMe disks residing in multiple remote hosts. Learn how we use the memory-mapping capabilities of PCIe non-transparent bridges to set up efficient I/O data paths between GPUs and disks that are attached to different root complexes (hosts) in a PCIe network. We'll demonstrate how our solution can initiate remote disk I/O from within a CUDA kernel. We will also compare our approach to state-of-the-art NVMe over fabrics and share our results for running a distributed workload on multiple GPUs using a remote disk.  Back
 
Topics:
Performance Optimization, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9563
Streaming:
Download:
Share:
 
Abstract:
Learn how GPUs can be time-shared between multiple hosts connected in a PCIe cluster using a method called device lending. Unlike approaches for sharing GPUs that typically require specific programming models, device lending makes a GPU appear to the operating system as if it is locally installed. This allows the GPU to be controlled and used by a remote host without any modifications to existing software. We'll present how device lending is implemented using standard PCIe and non-transparent bridging. As a proof-of- concept, we accelerate EIR, a computer-aided medical diagnosis system using machine learning and computer vision to do polyp detection, from being an offline tool to giving real-time feedback by dynamically borrowing remote GPU resources.
Learn how GPUs can be time-shared between multiple hosts connected in a PCIe cluster using a method called device lending. Unlike approaches for sharing GPUs that typically require specific programming models, device lending makes a GPU appear to the operating system as if it is locally installed. This allows the GPU to be controlled and used by a remote host without any modifications to existing software. We'll present how device lending is implemented using standard PCIe and non-transparent bridging. As a proof-of- concept, we accelerate EIR, a computer-aided medical diagnosis system using machine learning and computer vision to do polyp detection, from being an offline tool to giving real-time feedback by dynamically borrowing remote GPU resources.  Back
 
Topics:
Data Center & Cloud Infrastructure, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7281
Download:
Share:
 
 
Previous
  • Amazon Web Services
  • IBM
  • Cisco
  • Dell EMC
  • Hewlett Packard Enterprise
  • Inspur
  • Lenovo
  • SenseTime
  • Supermicro Computers
  • Synnex
  • Autodesk
  • HP
  • Linear Technology
  • MSI Computer Corp.
  • OPTIS
  • PNY
  • SK Hynix
  • vmware
  • Abaco Systems
  • Acceleware Ltd.
  • ASUSTeK COMPUTER INC
  • Cray Inc.
  • Exxact Corporation
  • Flanders - Belgium
  • Google Cloud
  • HTC VIVE
  • Liqid
  • MapD
  • Penguin Computing
  • SAP
  • Sugon
  • Twitter
Next