Coprocessor

A computer has a main brain.

Sometimes it needs a helper. This helper is called a coprocessor. It does hard jobs very fast. This helps the main brain work better.

One helper does math. It makes big math tasks much faster. This is good for science work.

Other helpers work on pictures. They help make 3D games look real. This is a big job for a computer.

Some helpers handle sound. They make music and noises. This lets the main brain do other things.

Today, many helpers live inside the main brain. They work together to make computers fast.

A computer has a main brain called a CPU.

Sometimes the CPU needs a helper for hard tasks. This helper is called a coprocessor. It helps the main brain work faster.

One type of helper does math. These are called floating-point units, or FPUs. They handle complex math with decimal points. In the 1980s, people bought these for science work. They could make math work fifty times faster.

Other helpers work on pictures. These are called graphics processing units, or GPUs. They help make 3D games look real. They take the heavy load off the CPU. Some helpers also handle sound or internet tasks.

In the past, these helpers were separate parts. You could plug them into a computer. Now, most helpers live inside the main CPU chip. This makes computers smaller and cheaper. But some special helpers still live on their own. They help with things like artificial intelligence. This lets computers learn to see and think.

A computer uses a main brain called a CPU.

Sometimes the CPU needs a helper for very hard jobs. This helper is called a coprocessor. It works alongside the main processor to finish tasks. This can make the whole computer work much faster. Using a coprocessor also helps people save money. They only buy the extra help if they truly need it.

Coprocessors work in different ways to help the CPU. Some helpers follow the CPU's direct instructions very closely. Other coprocessors act more like independent brains. They can work on their own without waiting for the CPU. A common way they work is through direct memory access. This is when the CPU builds a list of commands. Then the coprocessor follows that list to do the work.

In the past, people used separate systems for big computers. These systems were called Channel I/O. They helped the main computer focus on its most important jobs. Math helpers first appeared in desktop computers during the 1970s. They became very common throughout the 1980s and the 1990s. Before these helpers, computers used software to do hard math. A real math coprocessor could do these tasks many times faster.

Many famous chips helped make computers better for science. The Intel 8087 was a very popular math helper. It could make math work about fifty times faster. It was often used for computer-aided design or engineering. Other companies like Motorola and Weitek also made math helpers. Some helpers were small chips you plugged into a socket. Others were part of the main computer system.

Today, we see coprocessors in many things we use. Graphics processing units, or GPUs, are very common now. They help make 3D graphics in games look realistic. Some mobile devices even have special helpers for sensors. Apple uses motion coprocessors in some of its devices. Some new chips even help with artificial intelligence. These special chips help computers learn to see and think. They are still used to make machines much smarter.

A coprocessor is a specialized computer processor designed to supplement the functions of a primary processor, known as the Central Processing Unit (CPU). While the CPU acts as the main brain of a computer, it may struggle with specific, intensive tasks. A coprocessor takes these heavy workloads, such as floating-point arithmetic, graphics, or cryptography, and handles them separately. By offloading these tasks, the system can achieve much higher performance. This design also allows for customization. Customers can choose to pay for extra performance only if their specific work requires it.

Coprocessors function with varying degrees of autonomy. Some, like Floating-Point Units (FPUs), rely on direct control from the CPU. They receive instructions that are embedded directly into the CPU's instruction stream. Other coprocessors act as independent processors. These can work asynchronously, meaning they do not have to wait for the CPU to finish a task before starting their own. A common method for managing these independent units is Direct Memory Access (DMA). In this process, the host CPU builds a command list, and the coprocessor follows it to process data.

The history of offloading tasks began with mainframe computers. These large systems used Channel I/O to delegate input and output tasks to separate systems. By using simple sub-processors for time-consuming I/O formatting, the main mainframe could focus on its primary processing. In the 1970s, math coprocessors for floating-point arithmetic first appeared in desktop computers. Before these chips, early 8-bit and 16-bit processors had to use software to perform complex math. This was much slower than using dedicated hardware. By the 1980s and early 1990s, these math coprocessors became common tools for engineers and scientists.

During the era of 8-bit and 16-bit computing, several famous chips emerged. The Intel 8087 was a highly popular FPU for the original IBM PC. It was used heavily for computer-aided design (CAD) and intensive mathematical calculations. In that specific architecture, the 8087 could speed up floating-point arithmetic by approximately fiftyfold. Other companies provided alternatives, such as Motorola with the 68881 and Weitek. Weitek processors used a different instruction set and different sockets than Intel. They also lacked certain transcendental functions, such as trigonometric math, which required special software libraries to function.

As microprocessor technology advanced, the way coprocessors were built changed significantly. In the early days, math coprocessors were often separate chips that users plugged into a socket. For example, the Intel 80386 used an optional 80387 math coprocessor. However, by the time the Intel 80486 arrived, floating-point hardware was being integrated directly onto the main processor chip. This integration happened because the cost of adding these functions decreased. Additionally, as processor speeds reached the gigahertz range, it became difficult to connect separate chips on a circuit board. High speeds created challenges with power consumption and radio-frequency interference.

Modern computing relies heavily on specialized coprocessors for different tasks. Graphics Processing Units (GPUs) are now standard, providing the power needed for realistic 3D graphics in games. In the past, some sound cards included processors for digital multichannel mixing. In 2006, AGEIA introduced the PhysX PPU to handle complex physics computations. Eventually, Nvidia purchased the company and moved this functionality into the GPU software. We also see coprocessors in mobile devices. Apple uses motion coprocessors like the M7 and M8 to handle sensor data. Many modern smartphones now include AI chips to accelerate artificial neural networks for vision tasks.

Coprocessors continue to push the limits of what computers can achieve. In supercomputing, the China Matrix 2000 is a 128-core coprocessor. It was used to upgrade the Tianhe-2 supercomputer. This addition helped the system reach speeds of 95 petaflops. Even in specialized fields, custom coprocessors can be made using Field-Programmable Gate Arrays (FPGAs). These allow for very specific acceleration of tasks like digital signal processing. While many functions have moved inside the main CPU, specialized units remain vital for the next generation of computing power.