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Data structure alignment is the way data is arranged and accessed in computer memory. It consists of three separate but related issues: data alignment, data structure padding, and packing. The CPU in modern computer hardware performs reads and writes to memory most efficiently when the data is naturally aligned, which generally means that the data's memory address is a multiple of the data size. For instance, in a 32-bit architecture, the data may be aligned if the data is stored in four consecutive bytes and the first byte lies on a 4-byte boundary. Data alignment is the aligning of elements according to their natural alignment. To ensure natural alignment, it may be necessary to insert some padding between structure elements or after the last element of a structure. For example, on a 32-bit machine, a data structure containing a 16-bit value followed by a 32-bit value could have 16 bits of padding between the 16-bit value and the 32-bit value to align the 32-bit value on a 32-bit boundary. Alternatively, one can pack the structure, omitting the padding, which may lead to slower access, but uses three quarters as much memory. Although data structure alignment is a fundamental issue for all modern computers, many computer languages and computer language implementations handle data alignment automatically. Fortran, Ada, PL/I, Pascal, certain C and C++ implementations, D, Rust, C#, and assembly language allow at least partial control of data structure padding, which may be useful in certain special circumstances. A memory address a is said to be n-byte aligned when a is a multiple of n (where n is a power of 2). In this context, a byte is the smallest unit of memory access, i.e. each memory address specifies a different byte. An n-byte aligned address would have a minimum of log2(n) least-significant zeros when expressed in binary. The alternate wording b-bit aligned designates a b/8 byte aligned address (ex. 64-bit aligned is 8 bytes aligned). A memory access is said to be aligned when the data being accessed is n bytes long and the datum address is n-byte aligned.
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will explore various ways to implement a system
that changes the voice of a speaker. Typical applications for these
techniques, strictly sorted by plausibility, include international spy
missions and prank telephone calls, and devices such as the one
displayed here can be easily bought on the web... or in a novelty shop.
No description has been provided for t [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will look at the practical issues associated to
plotting the DFT and in particular the DFT of real-world signals. We
will examine how to map the DFT coefficients to real-world frequencies
and we will investigate the frequency resolution of the DFT and the
effects of zero padding.
In [1]:
[2]Paolo Prandoni, [3]LCAV, EPFL
This notebook shows a simple way to process audio files (in WAV format)
in a block-by-block fashion; this is useful in two cases
1. when you want to process a data stream in real time but you can
accept a small processing delay; in this case a buffered approach
can yield computational gains
2. when you need to process a large file that does not fit entirely
into [2]Paolo Prandoni, [3]LCAV, EPFL
The concept of "basis" for a vector space is one of the most profound
and fruitful ideas in linear algebra. Basis vectors are the "building
blocks" that all other vectors are built from; by "disassembling" a
vector into a linear combination of basis elements we are able to "look
inside" the vector and highlight many of its relevant features.
A vector space has an infinite number o