1. The Case for Operating System Services on GPUs
GPUfs

2. Why I chose this article
GPUs are increasing in performance compared to stagnating CPUs
I’ve used dedicated programs for GPUs before
It brings multi-threaded programs to a whole new level

3. What is GPUfs?
A software layer providing native support for accessing host files on discrete GPUs

4. Background GPUs are built up of multiprocessors
GPUs are structured for parallelism
No OS integration support for GPUs
Used similarly to a function call, for operations
All functions for GPUs had to be hand written and fine tuned.

5. GPUfs Thesis We have this incredible hardware
How can we tap into it
What is preventing us from using it
Why is GPUfs the answer
“The time has come to provide GPU programs the useful system services CPU code already enjoys.“

6. Where is GPUfs currently?
GPUs are just peripherals
Discrete vs Hybrid
“GPUfs is a system software co-resident with GPU programs but is less intrusive than a complete operating system in that it has no active continuously running components on the GPU”.

7. What needs to be addressed?
Functions that accomplish more
Virus scanning, searches
GPUs are mathematically faster
But still require CPU interference
Big Three
Separate Memory
Massive Parallelism
Non-preemptive hardware scheduling
Main focus has only been a file-system layer

8. My thoughts When will GPUfs become important
Discrete GPUs are still relevant
GPUs are used like co-processors
When would I need a GPU-CPU partnership

9. Your thoughts
Any questions?