Graphic Cards වැඩ කරන විදිහ

[thomian]

 

[delmar]

Thank you for sharing

 

[Schrodinger Cat]

bump

 

[AnuradhaRa]

 

[TonyMontana83]

Gpu hodai ethakota cpu walata wada?

 

[AnuradhaRa]

Gpu hodai ethakota cpu walata wada?

calculation වලට හොදයි

The CPU handles all the tasks required for all software

GPU, on the other hand, supports the CPU to perform concurrent calculations. A GPU can complete simple and repetitive tasks much faster because it can break the task down into smaller components and finish them in parallel.

Processor එකක් ඇතුලෙ වැඩ කාරයො දෙන්නෙක් ඉන්නව
Control Unit එකයි ALU එකයි

https://www.geeksforgeeks.org/difference-between-alu-and-cu/

මේ ටිකත් බලන්න @TonyMontana83 උඹත් ඉතිං මට ගොඩක් දේවල් කියල දෙනවනෙ

 

[TonyMontana83]

calculation වලට හොදයි

The CPU handles all the tasks required for all software

GPU, on the other hand, supports the CPU to perform concurrent calculations. A GPU can complete simple and repetitive tasks much faster because it can break the task down into smaller components and finish them in parallel.

Hmm.

 

[AnuradhaRa]

The main difference between a CPU (central processing unit) control unit and a GPU (graphics processing unit) control unit is that CPUs are general-purpose processors, while GPUs are more specialized:

• CPU
  CPUs are responsible for the main functions of a computer, such as managing system resources, coordinating programs, and handling complex decision-making. CPUs are versatile and excel at sequential processing.
• GPU
  GPUs are designed to handle multiple simple calculations simultaneously, such as complex mathematical operations and rendering graphics. GPUs are specialists that are more efficient at handling tasks that can be broken down into many identical, independent calculations.

GPUs have less complicated control units and arithmetic logic units (ALUs) than CPUs, and smaller caches. This allows GPUs to have more cores than CPUs.




CPUs and GPUs have a lot in common: both are critical computing engines, both are silicon-based microprocessors, and both handle data. But CPUs and GPUs have different architectures and are built for different purposes.

The CPU is suited for various tasks, especially those for which latency or per-core performance is important. A powerful execution engine, the CPU focuses its fewer cores on individual tasks and getting things done quickly. This makes it uniquely well-equipped for jobs ranging from serial computing, where only one task is executed at a time on a single processor, to running databases.

GPUs began as application-specific integrated circuits (ASICs) designed for specialized purposes such as accelerating graphics and 3D rendering tasks like gaming. Over time, these fixed-function engines became more programmable and more flexible. While graphics and hyper-realistic gaming visuals remain their principal function, GPUs have become more general-purpose parallel processors, able to execute many tasks simultaneously to handle a growing range of applications, including AI.

Today, it is no longer a question of CPU versus GPU. More than ever, you need both to meet your varied computing demands. The best results are achieved when the right tool is used for the job.