Perform real-time kernel tuning by managing system resources, measuring latency between events, and recording latency for analysis on applications with strict determinism requirements. It shows how KernTune identifies a system class and tunes the operating system for improved performance. Tune your workstations on the RHEL for Real Time kernel to achieve consistently low latency and a predictable response time on latency-sensitive applications. This thesis presents design and implementation details for KernTune. It uses a support vector machine (SVM) to identify the system class, and tunes the operating system for that specific system class. Intelligence (AI) oriented performance tuning. In this course, we tune the Linux kernel for performance. Tuning for our specific environment optimizes performance. These defaults are typically meant to get the. Tuning the kernel allows us to extract more performance out of the same hardware. A key aspect of KernTune is the notion of Artificial When any flavor of linux is installed, the kernel configuration is set to default values for every kernel setting. This thesis describes KernTune, a prototype tool that identifies the system class and improves system performance automatically. The idea of this loop is to continuously monitor certain performance metrics, and whenever these change, the system determines the new system class and dynamically adjusts tuning parameters for this new class. Our model for self-tuning operating system is based on a monitor-classify- adjust loop. Unfortunately, the system class can change when the running applications change. Well-trained system administrators are able to tune an operating system to achieve better system performance for a specific system class. Self-tuning has been an elusive goal for operating systems and is becoming a pressing issue for modern operating systems.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |