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https://issues.apache.org/jira/browse/MESOS-2262?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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chester kuo updated MESOS-2262:
-------------------------------
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 programming model : "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:
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.
> Adding GPGPU resource into Mesos, so we can know if any GPU/Heterogeneous
> resource are available from slave
> -----------------------------------------------------------------------------------------------------------
>
> Key: MESOS-2262
> URL: https://issues.apache.org/jira/browse/MESOS-2262
> Project: Mesos
> Issue Type: Task
> Components: slave
> Environment: OpenCL support env, such as OS X, Linux, Windows..
> Reporter: chester kuo
> Assignee: 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 programming model : "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.
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