[
https://issues.apache.org/jira/browse/MESOS-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
chester kuo updated MESOS-2262:
-------------------------------
Component/s: slave
framework
Description:
Extending Mesos to support Heterogeneous resource such as GPGPU/FPGA..etc as
computing resources in the data-center, OpenCL will be first target to add into
Mesos (support by all major GPU vendor) , I will reserve to support others such
as CUDA in the future.
In this feature, slave will be supported to do resources discover including but
not limited to,
(1) Heterogeneous Computing protocol type : "OpenCL". "CUDA", "HSA"
(2) Computing global memory (MB)
(3) Computing run time version , such as "1.2" , "2.0"
(4) Computing compute unit (double)
(5) Computing device type : GPGPU, CPU, Accelerator device.
(6) Computing (number of devices): (double)
The Heterogeneous resource isolation will be supported in the framework instead
of in the slave devices side, the major reason here is , the ecosystem , such
as OpenCL operate on top of private device driver own by vendors, only runtime
library (OpenCL) is user-space application, so its hard for us to do like Linux
cgroup to have CPU/memory resource isolation. As a result we may use run time
library to do device isolation and memory allocation.
(PS, if anyone know how to do it for GPGPU driver, please drop me a note)
Meanwhile, some run-time library (such as OpenCL) support to run on top of CPU,
so we need to use isolator API to notify this once it allocated.
was:
Try to add and extend to support OpenCL/GPU resource into Mesos so can we run
OpenCL application across Mesos cluster and utilize system's GPU resource
include memory , cpu..etc.
Why choose OpenCL instead of CUDA ?? Since OpenCL are supported by couple of
vendors include AMD, Intel , Samsung, Nvidia, Qualcomm..etc , and CUDA only
supported by Nvidia only.
Environment: OpenCL support env, such as OS X, Linux, Windows..
Issue Type: Task (was: Improvement)
Summary: Adding GPGPU resource into Mesos framework, so we can know if
any GPGPU resource are available for master (was: Add GPU resource into Mesos
framework, so we can know if any OpenCL/GPU resource are available for task
running.)
There is one discussion i like to have people input, in Mesos resource protocol
buffer message, it already support bunch of resources (such as CPU, memory ,
disk) , should we continue to use this resource message or defined a new
resources message for Heterogeneous devices to avoid having very long length of
resource message used currently.
Any comments , suggestions ?
> Adding GPGPU resource into Mesos framework, so we can know if any GPGPU
> resource are available for master
> ---------------------------------------------------------------------------------------------------------
>
> Key: MESOS-2262
> URL: https://issues.apache.org/jira/browse/MESOS-2262
> Project: Mesos
> Issue Type: Task
> Components: framework, slave
> Environment: OpenCL support env, such as OS X, Linux, Windows..
> Reporter: chester kuo
> Priority: Minor
>
> Extending Mesos to support Heterogeneous resource such as GPGPU/FPGA..etc as
> computing resources in the data-center, OpenCL will be first target to add
> into Mesos (support by all major GPU vendor) , I will reserve to support
> others such as CUDA in the future.
> In this feature, slave will be supported to do resources discover including
> but not limited to,
> (1) Heterogeneous Computing protocol type : "OpenCL". "CUDA", "HSA"
> (2) Computing global memory (MB)
> (3) Computing run time version , such as "1.2" , "2.0"
> (4) Computing compute unit (double)
> (5) Computing device type : GPGPU, CPU, Accelerator device.
> (6) Computing (number of devices): (double)
> The Heterogeneous resource isolation will be supported in the framework
> instead of in the slave devices side, the major reason here is , the
> ecosystem , such as OpenCL operate on top of private device driver own by
> vendors, only runtime library (OpenCL) is user-space application, so its hard
> for us to do like Linux cgroup to have CPU/memory resource isolation. As a
> result we may use run time library to do device isolation and memory
> allocation.
> (PS, if anyone know how to do it for GPGPU driver, please drop me a note)
> Meanwhile, some run-time library (such as OpenCL) support to run on top of
> CPU, so we need to use isolator API to notify this once it allocated.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
