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# 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

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• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 Consider a building that has two floors, with an escalator to carry people from one floor to the other. Ignoring queuing delays, the response time for a passenger is the mean time taken by the escalator to ascend or descend one floor. The throughput (bandwidth) is the mean number of passengers that can be loaded or per second. Suppose that an average of five people step on the escalator in one second, and that the escalator takes an average of 10 seconds to go up one floor. The response time for a passenger, therefore, is 10 seconds, and the throughput of the escalator is 5 passengers/second. Thus, the degree of parallelism, which is the mean number of passengers carried simultaneously, is 5*10=50. To see this, mark a passenger with a daub of red paint as she steps on the escalator. In the ten seconds that she takes to reach the top, we expect that fifty more passengers boarded the escalator. Thus, when she steps off, the escalator carries an average of fifty passengers, which is its degree of parallelism.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 Computation refers to the processing that can be done in a unit time. Using processors in parallel can increase computational power (as can waiting for a year or two― a reasonable rule of thumb is that computational speed doubles every 18 months!). We measure computation in millions of instructions per second (MIPS). We assume here that every instruction takes the same time to execute, which is more or less true for reduced-instruction-set (RISC) processors. In mid-1996, even low-end Intel 80486-class microprocessors processed about 30 million instructions per second. At the high end, Alpha processors from Digital Equipment processed more than 500 million instructions per second. With operating-system overheads, however, only about 80% of this rate is available to applications.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 We call a freely available resource an unconstrained resource, and a resource whose availability determines overall system performance a constrained resource. In this system, the link's bandwidth constrains the overall performance, as measured by the effective throughput of the link. This, therefore, is the constrained resource. In this example, the computer’s processing speed and money size are unconstrained resources.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。翻訳サイト

翻訳をお願いしたいです。コンピューター関係の書物の文章です。翻訳サイトのコピペはご遠慮ください。 Consider an airline reservation system, where agents from any part of the world can make a reservation for seats on any flight on any airline. One design for this system is to send all reservation requests to a single central computer. This design is simple, but has two problems. First, if the central computer crashes, every agent is affected. Second, as the number of agents increases, we need to expand the capacity of the central computer. However, the number of reservation requests, particularly during peak travel periods, may increase beyond the capacity of the largest computer that we can build or buy. Then, the response time suffers, and system performance degrades. We can solve this problem by replacing the central computer with a set of regional reservation center that coordinate among themselves to maintain a consistent view of the system state(such as whether a night is full or not). Then, as the number of reservation requests increases, we can just add another reservation center. We must, however, pay for this with a communication overhead for coordination, and a complex network to interconnect the regional reservation centers.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 Nevertheless, it is still, possible to identify some principles of good design that have withstood the test of time and are applicable in a variety of situations. In Section6.2, we will study some common resources, so that the reader can get some intuition in identifying them in real systems. We will then build up, in Section6.3, a set of tool to help us trade freely available (unconstrained) resources for scarce (constrained) ones. Properly applied, these tools allow us to match the design to the constraints at hand. Finally, in Section6.4, we will outline a methodology for performance analysis and tuning. This methodology helps pinpoint problems in a design and build a more efficient and robust system.

• 卒論に使用するため、翻訳をお願いしたいです。コンピューター関係の書物の

卒論に使用するため、翻訳をお願いしたいです。コンピューター関係の書物の文章です。 Consider a building that has two floors, with an escalator to carry people from one floor to the other. Ignoring queuing delays, the response time for a passenger is the mean time taken by the escalator to ascend or descend one floor. The throughput (bandwidth) is the mean number of passengers that can be loaded or per second. Suppose that an average of five people step on the escalator in one second, and that the escalator takes an average of 10 seconds to go up one floor. The response time for a passenger, therefore, is 10 seconds, and the throughput of the escalator is 5 passengers/second. Thus, the degree of parallelism, which is the mean number of passengers carried simultaneously, is 5*10=50. To see this, mark a passenger with a daub of red paint as she steps on the escalator. In the ten seconds that she takes to reach the top, we expect that fifty more passengers boarded the escalator. Thus, when she steps off, the escalator carries an average of fifty passengers, which is its degree of parallelism.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 If we could quantify and control every aspect of a system, then system design would be a relatively simple matter. Unfortunately there are several practical reasons why system design is both an art and a science. First, although we can quantitatively measure some aspects of system performance, such as throughput or response time, we cannot measure others, such as simplicity, scalability, modularity, and elegance. Yet a designer must make a series of trade- offs among these intangible quantities, appealing as much to good sense and personal choice as performance measurements. Second, rapid technological change can make constraint assumptions obsolete. A designer must not only meet the current set of design constraints, but also anticipate how future changes in technology might affect the design. The future is hard to predict, and a designer must appeal to instinct and intuition to make a design "future-proof." Third, market conditions may dictate that design requirements change when part of the design is already complete. Finally, international standards, which themselves change over time, may impose irksome and arbitrary constraints. These factors imply that, in real life, a designer is usually confronted with a complex, underspecified, multifactor optimization problem. In the face of these uncertainties, prescribing the one true path to system design is impossible.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。翻訳サイト

翻訳をお願いしたいです。コンピューター関係の書物の文章です。翻訳サイトのコピペはご遠慮ください。 In any system, some resources are less constrained than others. We call the most constrained resource in a system(or the binding constraint) its bottleneck. System performance improves if and only if we devote additional resources to a bottlenecked resource. Conversely, decreasing the amount of an unconstrained resource does not adversely affect performance. When we relieve one bottleneck, however, it is possible for another resource to become a bottleneck. Thus, we must remove the bottlenecks one by one until all the resources are equally constrained. We call such a system a balanced system. A balanced system is optimal, in that we fully utilize every component. However, in practice, we rarely achieve balanced systems. Rapid changes in technology, market constraints, and customer expectations mean that a system's components are almost constantly in flux, with the bottleneck moving from place to place in the system.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 A system designer must typically optimize one or more performance metrics given a set of resource constrains. A performance metric measures some aspect of a system's performance, such as throughput, response time, cost development time, or mean time between failures(we will define these metrics more formally in Section 6.2). A resource constraint is a limitation on a resource, such as time, bandwidth, or computing power, that the design must obey.

• 翻訳をお願いしたいです。コンピューター関係の書物の文章です。

翻訳をお願いしたいです。コンピューター関係の書物の文章です。 System design is important not only in computer systems, but also in other areas, such as automobile design. For example, a car designer might try to maximize the reliability of a car(measured in the mean time between equipment failures) that costs less than \$10,000 to build. In this example, the mean time between failures measures performance, and the resource constraint is money. In real life, of course, designs must try to simultaneously optimize many, possibly conflicting metrics (such as reliability, performance, and recyclability) while satisfying many constraints (such as the price of the car and the time allowed for the design).