Servers II. Ing. Jiří Kašpar prof. Ing. Pavel Tvrdík CSc.

Transcription

1 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 1/20 Servers II. Ing. Jiří Kašpar prof. Ing. Pavel Tvrdík CSc. Department of Computer Systems Faculty of Information Technology Czech Technical University in Prague Jiří Kašpar, Pavel Tvrdík, 2011 Advanced Computer System Architectures, MI-POA, 03/2011, Lecture 6 Evropský sociální fond Praha & EU: Investujeme do vaší budoucnosti

2 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 2/20 Mid-range and High-end Servers Mid-range and High-end Servers What is a mid-range server? o A shared memory computer system scalable up to 8 or 16 CPUs. What is a high-end server? o A shared memory computer system scalable more than midrange server. Multi-core CPUs changed traditional server classification (low-end, mid-range, high-end).

3 Mid-range Servers Mid-range Servers All current major CPU families (x64 AMD and Intel, IBM Power, Intel Itanium, and Sun/Oracle Sparc) use direct CPU-to-CPU interconnects and integrated memory controllers. Differences can be found in: o cache organization (number of levels in a hierarchy, private or shared, and inclusive or non-inclusive) cache coherency protocol (snooping or directory based) o scalability and extensibility (max. number of CPUs, total amount of memory, max. number of I/O devices) Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 3/20

4 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 4/20 Mid-range Servers Further Differences Number of cores/threads per CPU Multithreading model: fine grained multithreading: Sun Sparc Niagara concurrent multithreading (on demand switching): Intel x64, Itanium symmetric multithreading: IBM Power, AMD x64

5 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 5/20 Fix Size Mid-range Servers Scalable in-a-box only. Fix Size Mid-range Servers Modular structure allows to add more CPU modules. A CPU module typically consists of one or two CPUs and attached memory. Scaling is limited by the number of CPU module slots.

6 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 6/20 Adaptively Scalable Servers Adaptively Scalable Servers Adaptively scalable servers consist of building blocks, which alone are complete servers. They allow to build low-end to mid-range sizes. One system can be scaled both: o horizontally (several independent building blocks) or o vertically (several building blocks form a single big server). Two implementation patterns: standalone server blocks connected by cables interconnected blade servers A building block has typically two CPUs.

7 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 7/20 Adaptively Scalable Servers Adaptively Scalable Servers Building blocks can be connected using CPU-to-CPU communication links. Topology of the interconnect depends on implementation and server size: ring, mesh, complete graph.

8 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 8/20 Server Consolidation Server Consolidation Servers are sized to be able to handle peak load. Different applications run in different time, usually: two peaks during a workday (before and after lunch), internet services in evening, batch jobs during night. There is a big amount of unused resources. System costs can be reduced by optimizing resource utilization (not only HW, but also SW, power, cooling, and management).

9 Server Consolidation Consolidation Algebra: = 12 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 9/20 Peaks for different work loads do not all happen at the same time. + = Two workloads each have an 8 CPU peak demand, but the sum of their peaks is 12 CPUs.

10 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 10/20 But... Consolidation Algebra: can be > 16 If there are workload dependencies or shared resources, result can be worse See Queueing Theory, 50 Lecture 3, slide 7. Be careful!! Server Consolidation

11 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 11/20 Adaptive Server Infrastructure Adaptive Server Infrastructure Aim of adaptive server infrastructure is to provide environment for effective server consolidation, i.e. isolation of consolidated environments with flexible resource redistribution. Adaptive Server Infrastructure combines several techniques: vertical server scaling (scaling up), server partitioning, and clustering.

12 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 12/20 Adaptive Server Infrastructure Server Partitioning We can divide a server in several ways, with different granularity: on natural architecture borders on HW building block boundaries in server firmware (isolated by HW), on logical architecture boundaries in server firmware and/or operating system (isolated by SW), on fraction of a resource using multiplexing in time. Techniques can provide: Server Partitioning more independent operating system instances or resource domains inside a single operating system.

13 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 13/20 Adaptive Server Infrastructure Hard Partitions Hard Partitions Uses isolation on natural architecture borders on HW building block boundaries (crossbar switch, mesh). Configuration is usually done in server firmware. Each partition can run different operating system. Hard partitions have direct access to I/O devices. Power can be switched on/off independently. Maintenance can be done on HW partition when others are running. Granularity: CPU, memory, and I/O building blocks. Used on mid-range and high-end servers.

14 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 14/20 Dynamic Hard Partitions Some Hard partition techniques allow dynamic reconfiguration of resources (when OS is running). Hot add CPU, memory and I/O or a whole building block. Hot swap CPU. Adaptive Server Infrastructure Hot remove CPU. Dynamic Hard Partitions This functionality, namely hot swap and remove operations, depends on operating system capabilities.

15 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 15/20 Adaptive Server Infrastructure Soft Partitioning Soft Partitioning Similar to hard partitions, but rather than firmware, it use coordination between operating system instances. Also divides a system on architecture boundaries, but in finer granularity. Each partition runs its own copy of operating system, usually the only one type of OS. Usually shares data paths, isolation is done in operating system. Soft partitions have direct access to I/O devices. Granularity: Single CPU core, # MB of memory, I/O slot.

16 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 16/20 Adaptive Server Infrastructure Virtual Machines Virtual machines are based on CPU time slicing technique implemented in virtualization monitor. Each virtual machine can run different operating system. Virtual Machines usually access I/O devices using virtualization monitor, several I/O virtualization techniques are available. Granularity: Fraction of CPU core, # MB of memory, fraction of I/O controller, virtualized device. More information in Lecture 10. Virtual Machines

17 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 17/20 Adaptive Server Infrastructure Processor Sets Processor Sets Processor sets (psets) can divide a single instance of operating system on CPU core boundaries. By this technique, a user can reserve some CPU cores for a set of processes. Processes can be specified by a user or an application.

18 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 18/20 Adaptive Server Infrastructure Resource Partitioning Resource Partitioning Process Resource Manager (PRM) can divide a single instance of an operating system on granularity of several percent of CPU core. By this technique a user can reserve CPU time, memory and I/O throughput for a set of processes. Implemented using different process scheduler (gang scheduler, class scheduler). Processes can be specified by a user or an application. PRM can be combined with security hardening technique (i.e., internal firewall in OS). Examples: OpenVMS class scheduler, Unix PRM, Sun Security Zones, HP Security Compartments,...

19 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 19/20 Adaptive Server Infrastructure Clusters and Virtual Machines Clusters and Virtual Machines will be discussed in detail later: Clusters in Lecture 8, Virtual Machines in Lecture 10. Clusters and Virtual Machines

20 Jiří Kašpar, Pavel Tvrdík (ČVUT FIT) Servers II. MI-POA, 2011, Lecture 6 20/20 Sources Sources Konstantin Selucky: HP Integrity New Magic. HP internal. Don Roy: IBM System x & BladeCenter.