TimeGraph: GPU Scheduling for Real-Time Multi-Tasking Environments

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1 TimeGraph: GPU Scheduling for Real-Time Multi-Tasking Environments Shinpei Kato*, Karthik Lakshmanan*, Raj Rajkumar*, and Yutaka Ishikawa** * Carnegie Mellon University ** The University of Tokyo

2 Graphics Applications

3 Graphics Processing Unit (GPU) NVIDIA GPU GeForce GTX simple cores L1 L1 L1 L1 L1 L1 L1 L2 Cache Device Memory CPU Host Memory

4 GFLOPS Peak Performance GTX GTX 285 GTX GTX GTX 480 GTX GTX 200 Q9650 E4300 E6850 X XE /3/4 2007/12/ /9/ /7/6 NVIDIA GPU Intel CPU

5 GFLOPS / Watt Peak Performance per Watt GTX 9800 GT GTX 280 GTX 285 GTX 480 GTX 580 NVIDIA GPU Intel CPU GTX 1 Q XE E4300 E6850 X /3/4 2007/12/ /9/ /7/6

6 General-Purpose Computing on GPU (GPGPU) 3-D On-line Game Autonomous Driving Virtual Reality 3-D Interface Computer Vision Scientific Simulation

7 Outline 1. Introduction 2. What s Problem 3. Our Solution TimeGraph 4. Evaluation 5. Summary

8 GPU Is Command-Driven CMD_HtoD CMD_HtoD CMD_LAUNCH CMD_DtoH Host Memory Host Memory Host Memory Host Memory GPU Code Input Data GPU Code Input Data GPU Code Input Data GPU Code Input Data Output Data copy copy copy GPU Code GPU Code Input Data GPU Code Input Data Output Data GPU Code Input Data Output Data Device Memory Device Memory Device Memory Device Memory

9 Multi-Tasking Problem High-priority task Low-priority task GPU driver GPU command CPU time GPU Blocked Blocked time

10 Relative frame-rate to standalone Impact of Interference Execute Compete with w/ Widget Engine (low workload) GPU workload) Execute Compete with w/ Bomb Clearspd (high (high GPU workload) Observe Frame Rate of OpenArena (3-D Game) on Linux NVIDIA Nouveau NVIDIA Nouveau GeForce 9500 GeForce GTX 285 NVIDIA proprietary driver Nouveau open-source driver

11 Outline 1. Introduction 2. What s Problem 3. Our Solution TimeGraph 4. Evaluation 5. Summary

12 TimeGraph Architecture Software Approach User Space Applications OpenGL/CUDA Library User-space GPU Driver Kernel Space TimeGraph GPU Command Queue Kernel-space GPU Driver Submission Interface IRQ Handler GPU Command Group High- Priority Notification GPU Command Scheduler GPU resource control GPU Reserve Manager GPU exec. time prediction GPU Command Profiler Interrupt Graphics Processing Unit (GPU) Device Space

13 Priority Support Predictable Response Time (PRT) Policy When GPU is not idle, GPU commands are queued When GPU gets idle, GPU commands are dispatched High-priority task GPU command Low-priority task Interrupt GPU driver CPU time GPU Overhead Prioritized correctly time

14 Priority Support High Throughput (HT) Policy When GPU is not idle, GPU commands are queued, only if priority is lower than current GPU context When GPU gets idle, GPU commands are dispatched High-priority task GPU command Low-priority task Interrupt GPU driver CPU time GPU Overhead reduced time

15 Reservation Support Posterior Enforcement (PE) Policy Enforce GPU resource usage optimistically Specify capacity (C) and period (P) per task (/proc/gpu/$task) CPU time Enforced Execution Budget GPU time C P C time

16 P Reservation Support Apriori Enforcement (AE) Policy Enforce GPU resource usage pessimistically Specify capacity (C) and period (P) per task (/proc/gpu/$task) CPU time Enforced Enforced GPU Predict Predict Predict Predict time Execution Budget C C time

17 GPU Execution Time Prediction History-based approach Search records of previous sequences of GPU commands that match the incoming sequences of GPU commands Works for 2-D but needs investigation for 3-D and Compute Please see the paper for the detail

18 Outline 1. Introduction 2. What s Problem 3. Our Solution TimeGraph 4. Evaluation 5. Summary

19 Experimental Setup GPU: NVIDIA GeForce 9800 GT CPU: Intel Xeon E5504 OS: Linux Kernel Nouveau open-source driver Benchmark: Phoronix Test Suite Including OpenGL 3-D game programs Gallium3D Demo Suite Including OpenGL 3-D widget and graphics-bomb programs

20 Average frame-rate (fps) Performance Protection Frame Rate of 3-D Game competing with Graphics Bomb in background No Timing TimeGraph Support Support OpenArena World of Padman Urban Terror Unreal Trounament Priority Support (High Priority -> 3-D Game) Priority & Soft PE Reservation Support Support (GPU Util. 10% -> Graphics Bomb) Priority & Hard AE Reservation Support Support (GPU Util. 10% -> Graphics Bomb) 3-D Game Application

21 Frames per Second Frames per Second Frames per Second Interference on Time Widget Engine #1 Widget Engine #2 Widget Engine #3 Widget Engine #1 Widget Engine #2 Widget Engine #3 Widget Engine #1 Widget Engine #2 Widget Engine # Elapsed Time (Second) No TimeGraph Support Elapsed Time (Second) Elapsed Time (Second) Priority Support (PRT) Priority Support (PRT) + Reservation Support (PE)

22 Average frame-rate (fps) Standalone Performance X server is assigned PRT policy No TimeGraph Support Priority Support (HT) 30 Priority Support (PRT) Priority & Reservation Support (PRT & PE) 0 OpenArena World of Padman Urban Terror Unreal Trounament Priority & Reservation Support (PRT & AE) 3-D Game Application Overhead is acceptable for protecting GPU

23 Outline 1. Introduction 2. What s Problem 3. Our Solution TimeGraph 4. Evaluation 5. Summary

24 Concluding Remarks TimeGraph enables prioritization and isolation for GPU applications in multi-tasking environments Device-driver solution: no modification to user-space Scheduling of GPU commands Reservation of GPU resource usage

25 Execution Time (ms) Current Status GPGPU support (collaboration with PathScale Inc.) Visit Making open-source fast and reliable It s getting competitive to the proprietary driver! Some result from our OSPERT 11 paper (*) below: Matrix Multiplication Launch HtoD DtoH NVIDIA GPU GeForce GTX NVIDIA Ours NVIDIA Ours NVIDIA Ours NVIDIA Ours NVIDIA Ours NVIDIA Ours NVIDIA Ours 16 x x x x x x x 1024 * Available at

26 Thank you for your attention! Questions?

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