Computer architecture is a set of rules and methods

COMPUTER ARCHITECTURE IS A SET OF RULES AND METHODS

In computer engineering, computer architecture is a set of rules and methods that describe the functionality, organization, and implementation of computer systems. Some definitions of architecture define it as describing the capabilities and programming model of a computer but not a particular implementation. In other definitions computer architecture involves instruction set architecture design, microarchitecture design, logic design, and implementation.

The purpose is to design a computer that maximizes performance while keeping power consumption in check, costs low relative to the amount of expected performance, and is also very reliable. For this, many aspects are to be considered which includes instruction set design, functional organization, logic design, and implementation. The implementation involves integrated circuit design, packaging, power, and cooling. Optimization of the design requires familiarity with compilers, operating systems to logic design, and packaging.

Dr. David A. Patterson has been teaching computer architecture at the University of California, Berkeley, since joining the faculty in 1977.

Like his co-author, Patterson is a Fellow of the American Academy of Arts and Sciences, the Computer History Museum, ACM, and IEEE, and he was elected to the National Academy of Engineering, the National Academy of Sciences, and the Silicon Valley Engineering Hall of Fame. He served on the Information Technology Advisory Committee to the US President, as chair of the Computer Science division in the Berkeley Electrical Engineering & Computer Science department, as chair of the Computing Research Association, and as President of ACM. This record led to Distinguished Service Awards from ACM and CRA.

What will the increased diversity in computer architectures mean for the numerical weather prediction community?

First, the good news. More choice means more competition which, in turn, brings lots of benefits. In a more competitive landscape, we see a faster rate of innovation, with better systems for us to buy and use. Greater competition also results in better price competitiveness, so we will be able to deliver more science within our fixed budgets.

Now the not-so-good news. Greater diversity in computer architectures can create a big challenge for scientific software developers. Even porting software between architectures that seem very similar, even between one generation of x86 and the next, can be more burdensome than one might expect. Porting between different instruction sets, such as x86 and Arm, may not be a much bigger step, especially in an age where most codes rely on standard C/C++ or Fortran compilers, but highly optimized codes with particular expectations of SIMD widths or cacheline sizes may cause unexpected problems. The challenge is significantly greater when porting from one kind of architecture to a very different one, such as from a CPU to a GPU, as anyone who’s tried this for a real production code can attest.

The common pitfall that needs to be avoided is to assume that your next target architecture is the only architecture that will ever matter. History clearly shows this is never true, but if one were to believe that the next version of a code only ever had to run on a certain CPU architecture or a specific GPU, then that code immediately suffers from a major disadvantage: it becomes locked into a single architectural family, and subject to the fortunes of that choice. Once locked in to one vendor or architecture, a code may be unable to exploit a big advance in another area, such as significantly faster or cheaper processors from another vendor, or may suffer from a processor line being delayed or cancelled altogether, as with Intel’s recent termination of the Xeon Phi roadmap.

In order to be in a strong position to exploit the benefits brought by a more diverse landscape of processors, scientific software needs to be portable – in terms of both function and performance. By performance portable, we mean that the code would perform both “well” and “similarly well” across the range of target architectures; this might mean the code achieves similar fractions of peak memory bandwidth if bandwidth bound, or it might achieve similar fractions of peak FLOP/s if compute bound etc.

Адрес публикации: https://www.prodlenka.org/metodicheskie-razrabotki/324403-computer-architecture-is-a-set-of-rules-and-m