VT GPGPU/DraftSurvey

EGI User Community GPGPU Survey

Overview

The use of General Purpose Graphics Processing Units (GPGPUs) or accelerator devices, such as Intel's Xeon Phi co-processor, over the past few years has resulted in a huge increase in their exploitation by all the major scientific disciplines. With three of the top 10 clusters in the current June 2012 Top500 supercomputers list using NVIDIA GPGPUs, we would expect the number of GPGPU deployments at grid resource centres to grow significantly over the next few years. Moreover

The purpose of this survey is to gauge how the users currently use, or intend to use, GPGPUs or other accelerated devices in Grid or hybrid Grid/Cloud environments, or whether they shall use grids for this purpose. In particular, we would like to determine if there is a specific need from the User Communities for a more tightly integrated GPGPU capability within the grid environment. In addition, we welcome further user comments and feedback on any other aspects.

All data collected from the survey feedback will be processed anonymously.

User Profile

Q1 Which Scientific Discipline do you work in?

Text Box

Q2 Do you currently use grid or cloud technologies?

Yes
No (Please comment why?)
Comment Box

Q3 Do you use GPGPU based applications for your scientific computations ?

Yes
No (Please comment why?)
Comment Box

Q4 What is the speed-up achieved compared with not-parallel computing?

Question Logic: if Q3 was Yes

Text box

Q5 Do you intend to use them within the next 18 months ?

No
Yes (Please comment the time frame e.g. 3 months)

Comment box

Q6 Would you like to access GPGPU based resources through the European Grid Infrastructure (EGI) ?

Yes
No (Please comment why?)

Comment box

Application Development

Please Answer this section if you have answered yes to Q3.

If you have any other use cases you would like to bring our attention, please send us an email to : vt-gpgpu_AT_egi.eu.

Q7 Do you develop or intend to develop any GPGPU based applications?

Yes
No (Comment why?)

Comment

Q7 What do you expect from high level programming languages abstractions to write parallel programs?

Q8 Is there a need for such languages?

Q9 What particular numerical methods would you like to use on GPGPUs?

Q11 What Application Programming Interface do/will you use? (e.g. CUDA, OpenCL, OpenACC, or Other) ANS; Text

Q12 Do you intend to develop code which depends on other application frameworks (e.g MPI, BLAST etc). If Yes, then please list an example. ANS; Yes + optional text or No

Q13 Are there any particular GPGPU applications/solvers/libraries/methods you would like to have on a GPGPU cluster?

Q14 Is there a need on the market to implement additional applications/solvers/libraries/methods?

Q15 Are you performing hybrid computations (CPU + GPU), or CPU is just used for IO, communication and computation managing?

Q16 If you have answered Q15 What is the optimal ratio between the number of GPUs and CPU cores for your application?

Resource Centres GPGPU administration

These questions are intended to be answered by Resource Centre Administrators. The goal here is determine how widespread GPGPUs are (or will be) provided in the infrastructure; how the site administrators configure these resources in the batch system/scheduler; allocation policies; how these GPGPU are made visible on the grid infrastructure, etc.

Q10 Does your site currently provide GPGPU resources or does it intend to provide GPGPU resources? ANS; Yes + optional text or No

Q11 Which LRMS (i.e batch system and job scheduler do you use)

Q12. How the GPU resources are seen from LRMS point of view:

a) manually configured consumable resource

b) the GPU management is natively supported by the LRMS

c) the LRMS is not aware of GPUs (i.e. user have to request whole node to get exclusive access to GPUs)

d) other?

Q13 Does every node has GPU or only a subset of them? ANS:YES/NO

Q14 Is access to GPGPU-enabled hosts restricted to specific users or groups?

Q15: Link to hardware description (number of GPU nodes, type of GPU devices, number of cards per node). ANS:TEXT

Q16: Link to end-user documentation (i.e. how to submit a GPU job). ANS:Text

Q17: Did you implement some additional mechanism to manage access to GPU devices (e.g. custom prolog/epilog scripts,http://sourceforge.net/projects/cudawrapper/, ...)? ANS:TEXT

Q18: If you are utilizing all GPU resources on a node, do you expect, to be an exclusive user on this node (cost of PCI-Express and RAM bandwidth sharing, etc.)?

Q19: Do you expect any particular network topology on the cluster or utilities to exchange the data between the nodes (for instance NVIDIA GPUDirect)?