No abstract

Programs written in concurrent object-oriented languages, especially ones that employ thread-safe reusable class libraries, can execute synchronization operations (lock, notify, etc.) at an amazing rate. Unless implemented with utmost care, synchronization can become a performance bottleneck. Furthermore, in languages where every object may have its own monitor, per-object space overhead must be minimized. To address these concerns, we have developed a meta-lock to mediate access to synchronization data. The meta-lock is fast (lock + unlock executes in 11 SPARCTM architecture instructions), compact (uses only two bits of space), robust under contention (no busy-waiting), and flexible (supports a variety of higher-level synchronization operations). We have validated the meta-lock with an implementation of the synchronization operations in a high-performance product-quality JavaTM virtual machine and report performance data for several large programs.

Twelve years have passed since VMware engineers first virtualized the x86 architecture. This technological breakthrough kicked off a transformation of an entire industry, and virtualization is now (once again) a thriving business with a wide range of solutions being deployed, developed and proposed. But at the base of it all, the fundamental quest is still the same: running virtual machines as well as we possibly can on top of a virtual machine monitor.We review how the x86 architecture was originally virtualized in the days of the Pentium II (1998), and follow the evolution of the virtual machine monitor forward through the introduction of virtual SMP, 64 bit (x64), and hardware support for virtualization to finish with a contemporary challenge, nested virtualization.

No abstract

Programs written in concurrent object-oriented languages, especially ones that employ thread-safe reusable class libraries, can execute synchronization operations (lock, notify, etc.) at an amazing rate. Unless implemented with utmost care, synchronization can become a performance bottleneck. Furthermore, in languages where every object may have its own monitor, per-object space overhead must be minimized. To address these concerns, we have developed a meta-lock to mediate access to synchronization data. The meta-lock is fast (lock + unlock executes in 11 SPARC™ architecture instructions), compact (uses only two bits of space), robust under contention (no busy-waiting), and flexible (supports a variety of higher-level synchronization operations). We have validated the meta-lock with an implementation of the synchronization operations in a high-performance product-quality Java™ virtual machine and report performance data for several large programs.

No abstract

The performance of automatic memory management may be improved if the policies used in allocating and collecting objects had knowledge of the lifetimes of objects. To date, approaches to the pretenuring of objects in older generations have relied on profile-driven feedback gathered from trace runs. This feedback has been used to specialize allocation sites in a program. These approaches suffer from a number of limitations. We propose an alternative that through efficient sampling of objects allows for on-line adaption of allocation sites to improve the efficiency of the memory system. In doing so, we make use of a facility already present in many collectors such as those found in Java™ virtual machines: weak references. By judiciously tracking a subset of allocated objects with weak references, we are able to gather the necessary statistics to make better object-placement decisions.

The performance of automatic memory management may be improved if the policies used in allocating and collecting objects had knowledge of the lifetimes of objects. To date, approaches to the pretenuring of objects in older generations have relied on profiledriven feedback gathered from trace runs. This feedback has been used to specialize allocation sites in a program. These approaches suffer from a number of limitations. We propose an alternative that through efficient sampling of objects allows for on-line adaption of allocation sites to improve the efficiency of the memory system. In doing so, we make use of a facility already present in many collectors such as those found in Java TM virtual machines: weak references. By judiciously tracking a subset of allocated objects with weak references, we are able to gather the necessary statistics to make better object-placement decisions.