Difference between revisions of "GPGPU-FedCloud"

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(How to use GPGPU on IISAS-GPUCloud)
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For EGI users:
 
For EGI users:
 
  Join EGI federated cloud https://wiki.egi.eu/wiki/Federated_Cloud_user_support#Quick_Start
 
  Join EGI federated cloud https://wiki.egi.eu/wiki/Federated_Cloud_user_support#Quick_Start
 +
 
  Get VOMS proxy certificate from fedcloud.egi.eu or any supported VO (voms-proxy-init --voms fedcloud.egi.eu -rfc)
 
  Get VOMS proxy certificate from fedcloud.egi.eu or any supported VO (voms-proxy-init --voms fedcloud.egi.eu -rfc)
 +
 
  Choose suitable gpu.* flavor (gpu.medium or gpu.large) (OCCI users: resource_tpl#6 and resource_tpl#7)
 
  Choose suitable gpu.* flavor (gpu.medium or gpu.large) (OCCI users: resource_tpl#6 and resource_tpl#7)
 +
 
  Choose suitable images (e.g. Ubuntu-14.4, OCCI users: os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6)
 
  Choose suitable images (e.g. Ubuntu-14.4, OCCI users: os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6)
 +
 
  Create a VM with selected image and flavor (OCCI users: occi  --endpoint  https://nova3.ui.savba.sk:8787/  --auth x509 --user-cred $X509_USER_PROXY --voms --action create --resource compute --mixin os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6 --mixin resource_tpl#6 --attribute occi.core.title="Testing GPU")
 
  Create a VM with selected image and flavor (OCCI users: occi  --endpoint  https://nova3.ui.savba.sk:8787/  --auth x509 --user-cred $X509_USER_PROXY --voms --action create --resource compute --mixin os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6 --mixin resource_tpl#6 --attribute occi.core.title="Testing GPU")
 +
 
  Log in the VM and use it as your own GPU server.
 
  Log in the VM and use it as your own GPU server.
  
 
For other users:
 
For other users:
 
  Contact with cloud_admin _at_ savba.sk to get account and access to full-featured graphical portal
 
  Contact with cloud_admin _at_ savba.sk to get account and access to full-featured graphical portal
 
 
 
 
 
 
 
 
  
 
= Progress =
 
= Progress =

Revision as of 15:35, 10 October 2015

EGI-Engage project: Main page WP1(NA1) WP3(JRA1) WP5(SA1) PMB Deliverables and Milestones Quality Plan Risk Plan Data Plan
Roles and
responsibilities
WP2(NA2) WP4(JRA2) WP6(SA2) AMB Software and services Metrics Project Office Procedures



Objective

To provide support for accelerated computing in EGI-Engage federated cloud.


Participants

Viet Tran (IISAS)

Jan Astalos (IISAS)

Miroslav Dobrucky (IISAS)

Current status

A working site with GPGPU in EGI federated cloud

HW configuration:

IBM dx360 M4 server with two NVIDIA Tesla K20 accelerators.
Ubuntu 14.04.2 LTS with KVM/QEMU, PCI passthrough virtualization of GPU cards.

SW configuration:

Base OS: Ubuntu 14.04.2 LTS
Hypervisor: KVM
Middleware: Openstack Kilo

EGI federated cloud

GOCDB: IISAS-GPUCloud, https://goc.egi.eu/portal/index.php?Page_Type=Site&id=1485
Openstack endpoint: https://keystone3.ui.savba.sk:5000/v2.0
OCCI endpoint: https://nova3.ui.savba.sk:8787
Supported VOs: fedcloud.egi.eu, ops, dteam, moldyngrid

How to use GPGPU on IISAS-GPUCloud

For EGI users:

Join EGI federated cloud https://wiki.egi.eu/wiki/Federated_Cloud_user_support#Quick_Start
Get VOMS proxy certificate from fedcloud.egi.eu or any supported VO (voms-proxy-init --voms fedcloud.egi.eu -rfc)
Choose suitable gpu.* flavor (gpu.medium or gpu.large) (OCCI users: resource_tpl#6 and resource_tpl#7)
Choose suitable images (e.g. Ubuntu-14.4, OCCI users: os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6)
Create a VM with selected image and flavor (OCCI users: occi  --endpoint  https://nova3.ui.savba.sk:8787/  --auth x509 --user-cred $X509_USER_PROXY --voms --action create --resource compute --mixin os_tpl#3e1ad5a5-4d5a-4dbb-8b93-5c329129d3e6 --mixin resource_tpl#6 --attribute occi.core.title="Testing GPU")
Log in the VM and use it as your own GPU server.

For other users:

Contact with cloud_admin _at_ savba.sk to get account and access to full-featured graphical portal

Progress

  • May 2015
    • Review of available technologies
    • GPGPU virtualisation in KVM/QEMU
    • Performance testing of passthrough
HW configuration: 
IBM dx360 M4 server with two NVIDIA Tesla K20 accelerators.
Ubuntu 14.04.2 LTS with KVM/QEMU, PCI passthrough virtualization of GPU cards.
Tested application:
NAMD molecular dynamics simulation (CUDA version), STMV test example (http://www.ks.uiuc.edu/Research/namd/).
Performance results:
Tested application runs 2-3% slower in virtual machine compared to direct run on tested server.
If hyperthreading is enabled on compute server, vCPUs have to be pinned to real cores so that
whole cores will be dedicated to one VM. To avoid potential performance problems, hyperthreading 
should be switched off.

  • June 2015
    • Creating cloud site with GPGPU support
Configuration: master node, 2 worker nodes (IBM dx360 M4 servers, see above)
Base OS: Ubuntu 14.04.2 LTS
Hypervisor: KVM
Middleware: Openstack Kilo
  • July 2015
    • Creating cloud site with GPGPU support
Cloud site created at keystone3.ui.savba.sk, master + two worker nodes, configuration reported above
Creating VM images for GPGPU (based on Ubuntu 14.04, GPU driver and libraries)
  • August 2015
    • Testing cloud site with GPGPU support
Performance testing and tuning with GPGPU in Openstack 
 - comparing performance of cloud-based VM with non-cloud virtualization and physical machine, finding discrepancies and tuning them
 - setting CPU flavor in Openstack nova (performance optimization) 
 - Adjusting Openstack scheduler
Starting process of integration of the site to EGI FedCloud
 - Keystone VOMS support being integrated
 - OCCI in preparation, installation planned in September
  • September 2015
 Continue integration to EGI-FedCloud
  • Next steps
 Full integration, certification and production support

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