VMware® Virtual Symmetric Multi-Processing (SMP) enhances virtual machine performance by enabling a single virtual machine to use multiple physical processors, simultaneously. A unique VMware feature, Virtual SMP™ enables virtualization of the most processor- and
resource-intensive enterprise applications such as databases, ERP and CRM.

How Is VMware Virtual SMP Used in the Enterprise?

• Create development and testing environments that are more realistic and can be quickly and easily deployed

• Run resource intensive applications in virtualized environments.

• Run enterprise application such as databases, and ERP or CRM, in virtual machines.

• Scale computing environments without adding new hardware. Allow multiple processors to work together on a workload and increase utilization of existing resources.

• Improve software development and deployment.

How Does VMware Virtual SMP Work?

VMware Virtual SMP makes it possible for a single virtual machine to span up to four physical processors, or CPUs. These processors share the same memory, and work on any task regardless of the location of the task in memory. Virtual SMP co-schedules non-idle
virtual processors synchronously while allowing over-commitment of the processors. Idle virtual processors can be de-scheduled with the guest operating system running inside the virtual machine and then re-used for other tasks. Virtual SMP periodically moves processing tasks between the available processors to re-balance the work load. Virtual SMP has built-in controls to minimize overhead on the system.

General Information

• Poor performance of servers (if any) can be attributed to too many CPUs (as the wait time for CPU can increase if there are too any CPUs e.g. for a ‘single’threaded’ app on a a multi-vcpu VM)….

• As long as the operating system is designed to support SMP then the operating system is responsible for balancing the processes among all the available CPUs as evenly as it can.  In most cases, adding more CPUs to an SMP system does not increase throughput in direct proportion to the new resources because workloads cannot always take advantage efficiently of multiple CPUs. There is also some overhead involved in sharing resources and scheduling processes. For example, a four-CPU SMP system is not four times as productive as a single-CPU system. The efficiency of a multiple-CPU SMP system, versus a single-CPU system, is defined by the workload’s ability to scale, or the workload’s scaling ratio. This scaling ratio varies for different workloads.

• SMP systems are also affected by the need for locking and synchronization of resources. Before a task can modify a shared data item, it must ensure that no other task will change the data item. This is usually done by means of a lock. While a process or thread is waiting to obtain a lock, it is not productive. Further, while a thread is waiting for the lock, some of its cache lines may be replaced. Thus, when the thread is scheduled again, it may experience higher memory latency. The operating system’s kernel contains many shared data items, so it must perform synchronization internally. Synchronization delays can occur even in an application program that does not share data with other programs because the kernel services have to serialize shared kernel data. In addition to lock contention, path length also increases because more code is being executed.

• The main advantage of deploying an SMP system is the ability to use multiple processors simultaneously to execute different tasks constituting a program, thereby increasing the throughput (for example, the number of transactions per second), compared to a single-CPU system. Only workloads that support parallelisation (including multiple processes or multiple threads that can run in parallel) can benefit from SMP. Single-threaded workloads can be scheduled to only one CPU at the time; and thus, cannot take advantage of additional CPUs being available. On the other hand, some modern applications with significant computational components have built in multi-threaded structures and a high scalability ratio. Good examples of the latter are Microsoft® SQL Server and Microsoft Exchange. Microsoft recommends deploying these applications on SMP systems with at least two CPUs