von Neumann architecture
The von Neumann architecture—also known as the von Neumann model or Princeton architecture—is a computer architecture based on a 1945 description by John von Neumann, and by others, in the First Draft of a Report on the EDVAC.[1] The document describes a design architecture for an electronic digital computer with these components:
See also: Stored-program computer and Universal Turing machine § Stored-program computer
The term "von Neumann architecture" has evolved to refer to any stored-program computer in which an instruction fetch and a data operation cannot occur at the same time (since they share a common bus). This is referred to as the von Neumann bottleneck, which often limits the performance of the corresponding system.[3]
The von Neumann architecture is simpler than the Harvard architecture (which has one dedicated set of address and data buses for reading and writing to memory and another set of address and data buses to fetch instructions).
A stored-program computer uses the same underlying mechanism to encode both program instructions and data as opposed to designs which use a mechanism such as discrete plugboard wiring or fixed control circuitry for instruction implementation. Stored-program computers were an advancement over the manually reconfigured or fixed function computers of the 1940s, such as the Colossus and the ENIAC. These were programmed by setting switches and inserting patch cables to route data and control signals between various functional units.
The vast majority of modern computers use the same hardware mechanism to encode and store both data and program instructions, but have caches between the CPU and memory, and, for the caches closest to the CPU, have separate caches for instructions and data, so that most instruction and data fetches use separate buses (split-cache architecture).
History[edit]
The earliest computing machines had fixed programs. Some very simple computers still use this design, either for simplicity or training purposes. For example, a desk calculator (in principle) is a fixed program computer. It can do basic mathematics, but it cannot run a word processor or games. Changing the program of a fixed-program machine requires rewiring, restructuring, or redesigning the machine. The earliest computers were not so much "programmed" as "designed" for a particular task. "Reprogramming"—when possible at all—was a laborious process that started with flowcharts and paper notes, followed by detailed engineering designs, and then the often-arduous process of physically rewiring and rebuilding the machine. It could take three weeks to set up and debug a program on ENIAC.[4]
With the proposal of the stored-program computer, this changed. A stored-program computer includes, by design, an instruction set, and can store in memory a set of instructions (a program) that details the computation.
A stored-program design also allows for self-modifying code. One early motivation for such a facility was the need for a program to increment or otherwise modify the address portion of instructions, which operators had to do manually in early designs. This became less important when index registers and indirect addressing became usual features of machine architecture. Another use was to embed frequently used data in the instruction stream using immediate addressing.
Capabilities[edit]
On a large scale, the ability to treat instructions as data is what makes assemblers, compilers, linkers, loaders, and other automated programming tools possible. It makes "programs that write programs" possible.[5] This has made a sophisticated self-hosting computing ecosystem flourish around von Neumann architecture machines.
Some high level languages leverage the von Neumann architecture by providing an abstract, machine-independent way to manipulate executable code at runtime (e.g., LISP), or by using runtime information to tune just-in-time compilation (e.g. languages hosted on the Java virtual machine, or languages embedded in web browsers).
On a smaller scale, some repetitive operations such as BITBLT or pixel and vertex shaders can be accelerated on general purpose processors with just-in-time compilation techniques. This is one use of self-modifying code that has remained popular.
The First Draft described a design that was used by many universities and corporations to construct their computers.[16] Among these various computers, only ILLIAC and ORDVAC had compatible instruction sets.
The date information in the following chronology is difficult to put into proper order. Some dates are for first running a test program, some dates are the first time the computer was demonstrated or completed, and some dates are for the first delivery or installation.
Design limitations[edit]
Von Neumann bottleneck[edit]
The shared bus between the program memory and data memory leads to the von Neumann bottleneck, the limited throughput (data transfer rate) between the central processing unit (CPU) and memory compared to the amount of memory. Because the single bus can only access one of the two classes of memory at a time, throughput is lower than the rate at which the CPU can work. This seriously limits the effective processing speed when the CPU is required to perform minimal processing on large amounts of data. The CPU is continually forced to wait for needed data to move to or from memory. Since CPU speed and memory size have increased much faster than the throughput between them, the bottleneck has become more of a problem, a problem whose severity increases with every new generation of CPU.
The von Neumann bottleneck was described by John Backus in his 1977 ACM Turing Award lecture. According to Backus: