Hyper-threading is an optimization technique that allows you to run more than one thread on a single CPU core. It is Intel’s implementation of a technique known as simultaneous multithreading (SMT). This article covers only the basics of hyper-threading and is meant only as an introduction. The article tries to answer the following questions: What is hyper-threading? How does hyper-threading improve performance? What kind of performance improvements can we expect?

If we improve only one aspect of a computer system, the overall improvement in performance is limited by the extent the improved aspect is used. Amdahl’s Law addresses this limitation. The law was presented by Gene Amdahl in 1967. Amdahl’s paper focuses on the potential speedup that can be expected by using multiple processors. The law can be generalized to assess other areas of performance as well. For example, we can asses improvements in floating point performance, memory, etc.

In this article, I will describe one of the easiest methods for converting decimal numbers to binary. It is especially useful when there are multiple numbers to convert. Make a list of all the powers of 2, starting with 2 up to the number you want to convert. Please note that this is an inclusive range. So if the number is a power of two, it must be included in the list.

Conversion between hexadecimal and binary is quite easy; which is precisely why hexadecimal became rather important in computer science. This is despite being neither machine friendly like binary nor familiar to humans like decimal. About Hexadecimal Hexadecimal number system has 16 numerals. In addition to the ten decimal numerals [0..9], it also has A, B, C, D, E, and F. For example, in hexadecimal 10ten is written as Ahex and 16ten is written as 10hex.

On paper, we can represent a negative number by prefixing it with a minus sign. But, in computers, we will have to encode the sign in the number itself. This article discusses three prominent methods used for representing signed numbers in computers. All three methods work by treating the leftmost digit as a kind of sign bit. Contents Sign-Magnitude representation 1’s complement representation 2’s Complement Representation How does it work? Sign-Magnitude representation At first glance, the problem of representing signed numbers in a computer might seem quite straightforward.