Definition
Seeing the technical difficulties in cranking higher clock speed out of the present single core processors, dual core architecture has started to establish itself as the answer to the development of future processors. With the release of AMD dual core opteron and Intel Pentium Extreme edition 840, the month of April 2005 officially marks the beginning of dual core endeavors for both companies.
The transition from a single core to dual core architecture was triggered by a couple of factors. According to Moore's Law, the number of transistors (complexity) on a microprocessor doubles approximately every 18 months. The latest 2 MB Prescott core possesses more than 160 million transistors; breaking the 200 million mark is just a matter of time. Transistor count is one of the reasons that drive the industry toward the dual core architecture. Instead of using the available astronomically high transistor counts to design a new, more complex single core processor that would offer higher performance than the present offerings, chip makers have decided to put these transistors to use in producing two identical yet independent cores and combining them in to a single package.
To them, this is actually a far better use of the available transistors, and in return should give the consumers more value for their money. Besides, with the single core's thermal envelope being pushed to its limit and severe current leakage issues that have hit the silicon manufacturing industry ever since the transition to 90 nm chip fabrication, it's extremely difficult for chip makers (particulary Intel) to squeeze more clock speed out of the present single core design. Pushing for higher clock speeds is not a feasible option at present because of transistor current leakage. And adding more features into the core will increase the complexity of the design and make it harder to manage. These are the factors that have made the dual core option the more viable alternative in making full use of the amount of transistors available.
What is a dual core processor?
A dual core processor is a CPU with two separate cores on the same die, each with its own cache. It's the equivalent of getting two microprocessors in one. In a single-core or traditional processor the CPU is fed strings of instructions it must order, execute, then selectively store in its cache for quick retrieval. When data outside the cache is required, it is retrieved through the system bus from random access memory (RAM) or from storage devices. Accessing these slows down performance to the maximum speed the bus, RAM or storage device will allow, which is far slower than the speed of the CPU. The situation is compounded when multi-tasking. In this case the processor must switch back and forth between two or more sets of data streams and programs. CPU resources are depleted and performance suffers.
In a dual core processor each core handles incoming data strings simultaneously to improve efficiency. Just as two heads are better than one, so are two hands. Now when one is executing the other can be accessing the system bus or executing its own code. Adding to this favorable scenario, both AMD and Intel's dual-core flagships are 64-bit.
To utilize a dual core processor, the operating system must be able to recognize multi-threading and the software must have simultaneous multi-threadi0ng technology (SMT) written into its code. SMT enables parallel multi-threading wherein the cores are served multi-threaded instructions in parallel. Without SMT the software will only recognize one core. Adobe Photoshop is an example of SMT-aware software. SMT is also used with multi-processor systems common to servers.
An attractive value of dual core processors is that they do not require a new motherboard, but can be used in existing boards that feature the correct socket. For the average user the difference in performance will be most noticeable in multi-tasking until more software is SMT aware. Servers running multiple dual core processors will see an appreciable increase in performance.
Definition
Nanorobotics is an emerging field that deals with the controlled manipulation of objects with nanometer-scale dimensions. Typically, an atom has a diameter of a few Ångstroms (1 Å = 0.1 nm = 10-10 m), a molecule's size is a few nm, and clusters or nanoparticles formed by hundreds or thousands of atoms have sizes of tens of nm. Therefore, Nanorobotics is concerned with interactions with atomic- and molecular-sized objects-and is sometimes called Molecular Robotics.
Molecular Robotics falls within the purview of Nanotechnology, which is the study of phenomena and structures with characteristic dimensions in the nanometer range. The birth of Nanotechnology is usually associated with a talk by Nobel-prize winner Richard Feynman entitled "There is plenty of room at the bottom", whose text may be found in [Crandall & Lewis 1992]. Nanotechnology has the potential for major scientific and practical breakthroughs.
Future applications ranging from very fast computers to self-replicating robots are described in Drexler's seminal book [Drexler 1986]. In a less futuristic vein, the following potential applications were suggested by well-known experimental scientists at the Nano4 conference held in Palo Alto in November 1995:
" Cell probes with dimensions ~ 1/1000 of the cell's size
" Space applications, e.g. hardware to fly on satellites
" Computer memory
" Near field optics, with characteristic dimensions ~ 20 nm
" X-ray fabrication, systems that use X-ray photons
" Genome applications, reading and manipulating DNA
" Nanodevices capable of running on very small batteries
" Optical antennas
Nanotechnology is being pursued along two converging directions. From the top down, semiconductor fabrication techniques are producing smaller and smaller structures-see e.g. [Colton & Marrian 1995] for recent work. For example, the line width of the original Pentium chip is 350 nm. Current optical lithography techniques have obvious resolution limitations because of the wavelength of visible light, which is in the order of 500 nm. X-ray and electron-beam lithography will push sizes further down, but with a great increase in complexity and cost of fabrication. These top-down techniques do not seem promising for building nanomachines that require precise positioning of atoms or molecules.
Alternatively, one can proceed from the bottom up, by assembling atoms and molecules into functional components and systems. There are two main approaches for building useful devices from nanoscale components. The first is based on self-assembly, and is a natural evolution of traditional chemistry and bulk processing-see e.g. [Gómez-López et al. 1996]. The other is based on controlled positioning of nanoscale objects, direct application of forces, electric fields, and so on. The self-assembly approach is being pursued at many laboratories. Despite all the current activity, self-assembly has severe limitations because the structures produced tend to be highly symmetric, and the most versatile self-assembled systems are organic and therefore generally lack robustness. The second approach involves Nanomanipulation, and is being studied by a small number of researchers, who are focusing on techniques based on Scanning Probe Microscopy.
Definition
The Unified Modeling Language (UML) is a standard language for specifying, visualizing, constructing, and documenting the artifacts of software systems, as well as for business modeling and other non-software systems. The UML represents a collection of best engineering practices that have proven successful in the modeling of large and complex systems. The UML is a very important part of developing object oriented software and the software development process. The UML uses mostly graphical notations to express the design of software projects. Using the UML helps project teams communicate, explore potential designs, and validate the architectural design of the software.
Large enterprise applications - the ones that execute core business applications, and keep a company going - must be more than just a bunch of code modules. They must be structured in a way that enables scalability, security, and robust execution under stressful conditions, and their structure - frequently referred to as their architecture - must be defined clearly enough that maintenance programmers can (quickly!) find and fix a bug that shows up long after the original authors have moved on to other projects. That is, these programs must be designed to work perfectly in many areas, and business functionality is not the only one (although it certainly is the essential core). Of course a well-designed architecture benefits any program, and not just the largest ones as we've singled out here.
We mentioned large applications first because structure is a way of dealing with complexity, so the benefits of structure (and of modeling and design, as we'll demonstrate) compound as application size grows large. Another benefit of structure is that it enables code reuse: Design time is the easiest time to structure an application as a collection of self-contained modules or components. Eventually, enterprises build up a library of models of components, each one representing an implementation stored in a library of code modules.
Modeling
Modeling is the designing of software applications before coding. Modeling is an Essential Part of large software projects, and helpful to medium and even small projects as well. A model plays the analogous role in software development that blueprints and other plans (site maps, elevations, physical models) play in the building of a skyscraper. Using a model, those responsible for a software development project's success can assure themselves that business functionality is complete and correct, end-user needs are met, and program design supports requirements for scalability, robustness, security, extendibility, and other characteristics, before implementation in code renders changes difficult and expensive to make.
Surveys show that large software projects have a huge probability of failure - in fact, it's more likely that a large software application will fail to meet all of its requirements on time and on budget than that it will succeed. If you're running one of these projects, you need to do all you can to increase the odds for success, and modeling is the only way to visualize your design and check it against requirements before your crew starts to code.
Raising the Level of Abstraction:
Models help us by letting us work at a higher level of abstraction. A model may do this by hiding or masking details, bringing out the big picture, or by focusing on different aspects of the prototype. In UML 2.0, you can zoom out from a detailed view of an application to the environment where it executes, visualizing connections to other applications or, zoomed even further, to other sites. Alternatively, you can focus on different aspects of the application, such as the business process that it automates, or a business rules view. The new ability to nest model elements, added in UML 2.0, supports this concept directly.
