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https://github.com/kiritigowda/srtg-schedule
Dynamic schedule management framework for soft-real-time jobs on GPU based architectures
https://github.com/kiritigowda/srtg-schedule
amd aperiodic architectures cpus gpgpu gpu gpu-scheduler nvidia predictability schedule scheduler srtg-scheduler
Last synced: about 1 month ago
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Dynamic schedule management framework for soft-real-time jobs on GPU based architectures
- Host: GitHub
- URL: https://github.com/kiritigowda/srtg-schedule
- Owner: kiritigowda
- License: mit
- Created: 2017-02-20T16:18:46.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2023-09-07T23:18:29.000Z (over 1 year ago)
- Last Synced: 2024-02-29T12:27:25.461Z (10 months ago)
- Topics: amd, aperiodic, architectures, cpus, gpgpu, gpu, gpu-scheduler, nvidia, predictability, schedule, scheduler, srtg-scheduler
- Language: C
- Homepage: http://kiritigowda.com/SRTG-Schedule/
- Size: 34.6 MB
- Stars: 6
- Watchers: 3
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
[](https://opensource.org/licenses/MIT)
[](https://kiritigowda.com/SRTG-Schedule/)
[](https://travis-ci.org/kiritigowda/SRTG-Schedule)
[](https://codecov.io/gh/kiritigowda/SRTG-Schedule)
[](https://www.codefactor.io/repository/github/kiritigowda/srtg-schedule)
# Dynamic Schedule Management Framework For GPUs
## Soft-Real-Time GP-GPU Scheduler
A schedule management framework for aperiodic soft-real-time jobs that may be used by a CPU - GPU system designer/integrator to select, configure and deploy a suitable architectural platform and to perform concurrent scheduling of these jobs
[Soft-Real-Time GP-GPU Scheduler](SRTG-Scheduler) (SRTG-Scheduler) is a dynamic scheduler for aperiodic soft-real-time jobs on GPU based architectures, with a simple, easy-to-use command-line interface (CLI). The SRTG-Scheduler is provided under the [MIT license](https://opensource.org/licenses/MIT). It is currently supported on Windows, Linux, and macOS platforms.
### Latest SRTG-Scheduler
[](https://github.com/kiritigowda/SRTG-Schedule/releases)
## Dynamic schedule management framework for soft-real-time jobs on GPU based architectures
#### [GPUs](scheduler_info.md#graphics-processing-units-in-real-time) execute at higher frequencies
* Accelerates execution of jobs allocated to it
* Improves System response time
The above image compares FLOPs per Cycle improvements over the years [1]
#### [GPUs](scheduler_info.md#graphics-processing-units-in-real-time) are energy efficient
* Power needed for GPU to carry out an operation lesser than CPUs
* Ideal for use in real time embedded system
* Significant hardware and firmware challenges
* Executions are non-preemptive
* Low degree of controllability of cores
* Policies for scheduling Real-Time jobs
* Decoding the driver
* Managing the GPU as a resource
* Targeting a Multi-GPU model
This entire body of work assumes that only one kernel may execute on a GPU at a given time(partly due to lack of hardware support)
#### What's the problem?
Sending a single non-preemptive kernel on to a GPU, is under utilizing the GPU
#### Solution
Concurrent Kernels Execution on GPU [2]
* Safe concurrent kernels
* Performance boost
* Execution units available
Aims to develop a dynamic schedule management framework for soft-real-time
jobs on GPU based architectures.
We propose to exploit this basic idea to perform coarse grained scheduling of jobs on GCUs.
Our work lays emphasis on minimal programmer involvement.
A dynamic schedule management framework that is responsible for
* Keeping track of current and expected GUC availability
* Determining which kernel(s) to dispatch to the GPU at a given time
* Determining how many GCUs to assign for a given kernel.
#### Advantages
* GPU provides tremendous computational power under reasonable power/energy budgets
* Our work exploits concurrent kernel execution for real-time scheduling
* More economical than multi-GPU model
#### Results
* Dynamic schedule management [framework](SRTG-Scheduler#real-time-gpu-scheduler) for soft-real-time jobs
* Support for [a-periodic](SRTG-Scheduler#real-time-gpu-scheduler) and recurring (periodic) soft-real-time tasks.
* Smart GPU Memory Management
**note:**
* [1] [FLOPs per Cycle for CPUs, GPUs and Xeon Phis](https://www.karlrupp.net/2016/08/flops-per-cycle-for-cpus-gpus-and-xeon-phis/)
* [2] [Concurrent soft-real-time job execution on GPUs - Page 13 & 14](https://people.mpi-sws.org/~bbb/proceedings/rtas14-wip-proceedings.pdf)