Performance and scalability analysis- Distributed Computing

Performance metrics

  • CPU speed: Million Instructions Per Second (MIPS)
  • Network bandwidth: Megabits Per Second (Mbps)
  • Distributed systems throughput Tera floating-point operations per second (Tflops) Transactions per second (TPS) Job response time and network latency
  • Low latency and high bandwidth interconnection is preferred
  • System overhead is often attributed to OS boot time, compile time, I/O data rate, and the runtime support system QoS for Internet and web services, system availability and dependability, security

Dimensions of Scalability

  • The ability of a system, network, or process to handle a growing amount of work in a capable manner or its ability to be enlarged to accommodate that growth [wikipedia]
  • Size scalability: Achieving higher performance by increasing the machine size (processors, cache, memory, storage, …)
  • Software scalability:” Upgrades in the OS or compilers, adding mathematical and engineering libraries, porting new application software, and installing more user-friendly programming environments
  • Application scalability: Refers to matching problem size scalability with machine size scalability
  • Technology scalability: This refers to a system that can adapt to changes in building technologies

Technology scalability

When scaling a system design with new technology one must consider three aspects

  • Time scalability: Refers to the impact of new generation technology such as a processor on motherboard, power supply, …
  • Space scalability: Space is related to packaging and energy concerns. Technology scalability demands harmony and portability among suppliers
  • Heterogeneity: Refers to the use of hardware components or software packages from different vendors. Heterogeneity may limit the scalability