Virtual Memory Performance Research Articles

Least Recently Used Page Replacement using Last Use Distance (LRUL)

Virtual memory technique is used in modern OS which permits the execution of a program while it is partially available in memory thus providing an illusion of very large memory to the user and freeing the user from the concern of large program size. This uses a page replacement technique such as first in first out (FIFO), least recently used (LRU), optimal etc. to replace a page in memory when a frame is needed and no free frame is available in memory. Here page replacement policy severely affects the performance of virtual memory. It has been observed that LRU approximates optimal so LRU and its variants are quite common in use in operating system as a reasonable choice of page replacement algorithm. But LRU performs very poor by generating continuous page faults while accessing looping pattern if all the pages does not fit in the memory simultaneously. This paper presents a simple modified LRU algorithm called LRUL overcoming this problem using the concept of last use distance (LUD). It is observed that the new algorithm gives better results than LRU. General Terms Operating system, page replacement algorithm.

Virtual servers: real-world issues

The soaring power of server hardware, recently boosted by multicore processors, has focused IT manager's mind on how much power - both electrical and compute - they were wasting. In this article the author reveals that data servers running in software emulations of real hardware can slash the number of power-hungry computers needed in the enterprise - but the less tangible spin-offs might prove the real making of virtualisation. Suppliers working on virtualization extensions will not just make it easier to host operating systems, they will help with the performance of virtual memory and I/O.

Kohonen Self-Organizing Maps and Expert System for Network Virtual Memory Performance Prediction

A basic reason why we monitor the performance of a system is to define the overall state of the machine (It's Ok or It's slow etc). In other words to determine whether the system is experienceing a bottleneck or not. This paper investigates the application of Self Organizing Maps (SOM) and Expert System (ES) in the network performance management area. A system is proposed which collects data from certain server and processes the data in order to get knowledge concerning the current network performance or predicts the network performance. To demonstrate the applicability of the proposed method to network performance domain problems, a case study in virtual memory performance status (vmstat) domain is presented.

Implementing heap-object behavior prediction efficiently and effectively

Heap-allocated objects play an important role in many modern programs. Various results have shown the overall performance of these programs can be improved by increasing the reference locality of heap-allocated objects. In this paper we describe an approach that improves the virtual memory performance of allocation-intensive C programs by predicting the reference behavior and lifetime of heap objects as they are allocated. We further describe an implementation of our prediction algorithm and evaluate its performance on real programs. As part of our implementation, we present a low-overhead algorithm to minimize the cost of gathering run-time stack information. Finally, we show that an implementation of these algorithms has little overhead and can improve the virtual memory and TLB performance of programs substantially. Copyright © 2001 John Wiley & Sons, Ltd.

Memory system behavior of Java programs

This paper studies the memory system behavior of Java programs by analyzing memory reference traces of several SPECjvm98 applications running with a Just-In-Time (JIT) compiler. Trace information is collected by an exception-based tracing tool called JTRACE, without any instrumentation to the Java programs or the JIT compiler. First, we find that the overall cache miss ratio is increased due to garbage collection, which suffers from higher cache misses compared to the application. We also note that going beyond 2-way cache associativity improves the cache miss ratio marginally. Second, we observe that Java programs generate a substantial amount of short-lived objects. However, the size of frequently-referenced long-lived objects is more important to the cache performance, because it tends to determine the application's working set size. Finally, we note that the default heap configuration which starts from a small initial heap size is very inefficient since it invokes a garbage collector frequently. Although the direct costs of garbage collection decrease as we increase the available heap size, there exists an optimal heap size which minimizes the total execution time due to the interaction with the virtual memory performance.

Adaptive memory management and optimism control in time warp

It is widely believed that the Time Warp protocol for parallel discrete event simulation is prone to two potential problems: an excessive amount of wasted, rolled back computation resulting from “rollback thrashing” behaviors, and inefficient use of memory, leading to poor performance of virtual memory and/or multiprocessor cache systems. An adaptive mechanism is proposed based on the Cancelback memory management protocol for shared-memory multiprocessors that dynamically controls the amount of memory used in the simulation in order to maximize performance. The proposed mechanism is adaptive in the sense that it monitors the execution of the Time Warp program, and using simple models, automatically adjusts the amount of memory used to reduce Time Warp overheads (fossil collection, Cancelback, the amount of rolled back computation, etc.) to a manageable level. We describe an implementation of this mechanism on a shared memory, Kendall Square Research KSR-1, multiprocessor and demonstrate its effectiveness in automatically maximizing performance while minimizing memory utilzation, for several synthetic and benchmark discrete event simulation applications. We also demonstrate the adaptive ability of the mechanism by showing that it “tracks” the time-varying nature of a communication network simulation.

An adaptive memory management protocol for Time Warp parallel simulation

It is widely believed that Time Warp is prone to two potential problems: an excessive amount of wasted, rolled back computation resulting from “rollback thrashing” behaviors, and inefficient use of memory, leading to poor performance of virtual memory and/or multiprocessor cache systems. An adaptive mechanism is proposed based on the Cancelback memory management protocol that dynamically controls the amount of memory used in the simulation in order to maximize performance. The proposed mechanism is adaptive in the sense that it monitors the execution of the Time Warp program, automatically adjusts the amount of memory used to reduce Time Warp overheads (fossil collection, Cancelback, the amount of rolled back computation, etc.) to a manageable level. The mechanism is based on a model that characterizes the behavior of Time Warp programs in terms of the flow of memory buffers among different buffer pools. We demonstrate that an implementation of the adaptive mechanism on a Kendall Square Research KSR-1 multiprocessor is effective in automatically maximizing performance while minimizing memory utilization of Time Warp programs, even for dynamically changing simulation models.

A real-time garbage collector based on the lifetimes of objects

In previous heap storage systems, the cost of creating objects and garbage collection is independent of the lifetime of the object. Since objects with short lifetimes account for a large portion of storage use, it is worth optimizing a garbage collector to reclaim storage for these objects more quickly. The garbage collector should spend proportionately less effort reclaiming objects with longer lifetimes. We present a garbage collection algorithm that (1) makes storage for short-lived objects cheaper than storage for long-lived objects, (2) that operates in real time—object creation and access times are bounded, (3) increases locality of reference, for better virtual memory performance, (4) works well with multiple processors and a large address space.

Evaluation of efficiency in a virtual memory environment

The development of elaborate supervisory systems for the modern day computer has dictated a need for a means of evaluating the efficiency of the computing system under normal operating conditions. This paper defines a set of synthetic job streams which can be used to evaluate the performance of virtual memory computing systems under batch program conditions. An illustration of the use of these synthetic streams is presented in an empirical search for the optimum batch limit of a specific example of a virtual memory computer system. Limited tests are also presented to support the results of this study.

Experiments on Page Size, Program Access Patterns, and Virtual Memory Performance

The assumption about virtual memory systems that as overhead (time for access and software page management) decreases page size should be reduced is not alwayas good one. Recent experiments indicate that larger page sizes can provide better performance for programs that make highly localized use of memory space.