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Multicore system

• CPU with more than one core

• Cores operate as separate processor within a single chip

• Increase performance without raising the processor clock speed

Multiprocessor system

• Have more than one CPU

• Some machine combines two technologies, multicore and multiprocessor

(a) A shared-memory multiprocessor. (b) A message-passing multicomputer. (c) A wide area distributed system.

• Multiprocessor Systems are classified according to the manner of associating CPUs and memory units

– Uniform memory access (UMA) architecture

• Previously called tightly coupled multiprocessor

• Also called symmetrical multiprocessor (SMP)

• Examples: Balance system and VAX 8800

– Nonuniform memory access (NUMA) architecture

• Examples: HP AlphaServer and IBMNUMA-Q

– No-remote-memory-access (NORMA) architecture

• Example: Hypercube system by Intel

• Is actually a distributed system (discussed later)

Three bus-based multiprocessors. (a) Without caching. (b) With caching. (c) With caching and private memories.

• Unified Memory Access (UMA)

– also known as Symmetric MultiProcessors (SMP)

• Non-Unified Memory Access (NUMA)

• SIMILARITIES

– single memory space

– pitfall: Compared between shared memory and distributed memory.

• DIFFERENT

– access time

– # of processors

– bus vs. network implementation

• SISD (Single Instruction Single Data)

• Uniprocessors

• MISD (Multiple Instruction Single Data)

• Stream based processing

• SIMD (Single Instruction Multiple Data = DLP)

• Examples: Illiac-IV, CM-2 (Thinking Machines), Xetal (Philips), Imagine (Stanford), Vector machines, Cell architecture (Sony)

• Simple programming model

• Low overhead

• MIMD (Multiple Instruction Multiple Data)

• Examples: Sun Enterprise 5000, Cray T3D, SGI Origin,
Multi-core Pentiums, and many more….

• Figure 8-10. The TSL instruction can fail if the bus cannot be locked. These four steps show a sequence of events where the failure is demonstrated.

• Figure 8-11. Use of multiple locks to avoid cache thrashing.

Figure 8-12. Using a single data structure for scheduling a multiprocessor.

The three parts of gang scheduling:

Groups of related threads are scheduled as a unit, a gang.
All members of a gang run simultaneously, on different timeshared CPUs.
All gang members start and end their time slices together.

• Figure 8-14. Communication between two threads belonging to thread A that are running out of phase.

Characteristics of Embedded System

• Real-time operation:

– In many embedded systems, the correctness of a computation depends, in part, on the time at which it is delivered. Often, real-time. Constraints are dictated by external I/O and control stability requirements.

• Reactive operation:

– Embedded software may execute in response to external events. If these events do not occur periodically or at predictable intervals, the embedded software may need to take into account worst-case conditions and set priorities for execution of routines.

• Configurability:

• Because of the large variety of embedded systems, there is a large variation in the requirements, both qualitative and quantitative, for embedded OS functionalityfor execution of routines.

• I/O device flexibility:

• There is virtually no device that needs to be supported by all versions of the OS, and the range of I/O devices is large.

• Streamlined protection mechanisms:

• Embedded systems are typically designed for a limited, well-defined functionality

• Direct use of interrupts:

• General-purpose operating systems typically do not permit any user process to use interrupts directly

Purpose Built Embedded Operating System

• A significant number of operating systems have been designed from the ground up for embedded applications. Two prominent examples of this latter approach are eCos and TinyOS.

Specialized Embedded System

• Typically include

– Has a fast and lightweight process or thread switch

– Scheduling policy is real time and dispatcher module is part of scheduler instead of separate component.

– Has a small size

– Responds to external interrupts quickly; typical requirement is response time of less than 10 μs

– Minimizes intervals during which interrupts are disabled

– Provides fixed or variable-sized partitions for memory management as well as the ability to lock code and data in memory

– Provides special sequential files that can accumulate data at a fast rate To deal with timing constraints, the kernel provides bounded execution time for most primitives

– Maintains a real-time clock

eCos

• eCOS – Embedded Configurable Operating System

• Open Source, royalty free, real time O/S for embedded application

Configurability

• eCos configuration tool, which runs on Windows or Linux, is used to configure an eCos package to run on a target embedded system

• eCos package is structured hierarchically

eCos Component

• HAL – Harwarde Abstraction Layer

– HAL is software that presents a consistent API to the upper layers and maps upper-layer operations onto a specific hardware platform

• eCos Kernel

– Designed to meet the following objectives:

• Low interrupt latency: The time it takes to respond to an interrupt and begin executing an ISR.

• Low task switching latency: The time it takes from when a thread becomes available to when actual execution begins.

• Small memory footprint: Memory resources for both program and data are kept to a minimum by allowing all components to configure memory as needed.

• Deterministic behavior: Throughout all aspect of execution, the kernels performance must be predictable and bounded to meet real-time application requirements.

eCos Scheduler

• Bitmap Sheduler

– A bitmap scheduler supports multiple priority levels, but only one thread can exist at each priority level at any given time.

• Multilevel Queue Scheduler

– Supports up to 32 priority levels

– allows for multiple active threads at each priority level, limited only by system resources

Client Server Computing

• client/server environment is populated by clients and servers

• Each server in the client/server environment provides a set of shared services to the clients

• Client/server computing is typically distributed

• Computing

Client Server Envronment

Client Server Architecture

Three tiered Client Server Architecture

Middleware

• Middleware provides a layer of software tat enables uniform access to different systems

Service Oriented Architecture

• A form f client/server architecture

• Organizes business functions into modular structure

• Conssts of a set of services and a set of client applications that uses the services

SOA Architectural components

• Three types

– Service Provider

• A network node that provides a service interface for a software asset that manages a specific set of tasks

– Service requestor

• A network node that discovers and invokees other software services to provide a business solution

– Service Broker

• A specific kind of service that acts as a registry and allows for the lookup of service provider interfaces and service locations

Clustering

• An approac to provide high performance and high availability

• A cluster is a group of interconnected, whole computer working together as a unified computing resource (act as one machine)

Benefits of clustering

• Absolute scalability: It is possible to create large clusters that far surpass the power of even the largest stand-alone machines. A cluster can have dozens or even hundreds of machines, each of which is a multiprocessor.

• Incremental scalability: A cluster is configured in such a way that it is possible to add new systems to the cluster in small increments. Thus, a user can start out with a modest system and expand it as needs grow, without having to go through a major upgrade in which an existing small system is replaced with a larger system.

• High availability: Because each node in a cluster is a stand-alone computer, the failure of one node does not mean loss of service. In many products, fault tolerance is handled automatically in software.

• Superior price/performance: By using commodity building blocks, it is possible to put together a cluster with equal or greater computing power than a single large machine, at much lower cost.

Two nodes cluster