ABSTRACT:
In today’s world where technology plays a major part in the success of even every field and its
enhancing and getting stronger day by day. In early ages, we have single core CPU and then multicore
processors and now we have GPU which are built for graphics purpose works in parallelism. GPU has
given our PCs, more explicitly the gaming consoles the wide range of handling mind-boggling and
constant 3D illustrations that were viewed as for all intents and purposes difficult to accomplish only a
couple of years back. In this report, we will increase our knowledge about the GPU, what actually GPU is
and what they do and how they do and they have become so essential.
INTRODUCTION:
We are living in a world that requires 3D simulation as real as possible in computer graphics. The 3D
world needs a huge amount of computing power because of the bulk of information which is required
for it. The normal CPU can’t do all that by its self so GPU introduced which is responsible for the
computer graphics. GPUs are widely used nowadays and have lots of applications like a game console,
personal PCs, mobile phones, and workstations. The modern GPUs are doing great as the efficiency
increased due to their parallel structure for algorithms which are used to process the bulk of data.
The term GPU is introduced around 1980 and become popular in 1999 by Nvidia and become the worlds
first GPU. The main objective of a GPU, be that as it may, is to empower a representation of a 3D world
as sensibly as would be practical. So, these GPUs are intended to give extra computational power that is
altered explicitly to play out these 3D actions. GPUs turned out to be more mainstream as the interest
for realistic applications expanded. In the end, they wound up an improvement as well as a need for
ideal execution of a PC. Particular rationale chips currently permit video executions and quick graphics.
Numerous calculations outside the field of picture rendering and preparing are quickened by
information parallel handling, from general flag handling or material science recreation to
computational back or computational science.
According to its name GPU, it is not purely used for tasks that are only related to graphics. Due to its
high computing power, it is also capable to do complex resource intensive. Today’s technologies
machine learning and Artificial intelligence have become reality with GPU computing processing power.
The practical reason for a GPU at that point, is to give a different devoted illustrations asset, including a
designs processor and memory, to calm some of the weight off of the primary framework assets, to be
specific the Central Processing Unit, Primary Memory, and the System Bus, which would somehow or
another get soaked with graphical activities and I/O tasks. The conceptual objective of a GPU, be that as
it may, is to empower a portrayal of a 3D world as sensibly as could be allowed. So, these GPUs are
intended to give extra computational power that is redone explicitly to play out these 3D graphics.
The following sections will elaborate the need and importance of GPUs, its functionality, its
components, and methodology, we discuss its architecture and how the information process through it
and how it is so beneficial for 3D graphics.
METHODOLOGY:
In this paper, we worked on quantitative and qualitative research methods to understand the purpose
and functionality of GPU the components that are used in it to make it programmable and types of GPU.
And for the deep understanding of its working. The questioner was created and distributed among
peoples and the scientific persons that are involved in this technology to make the better understanding
of GPU. As complementary method, we conduct some interview of the technical person who is working
on it to know the importance of it today’s world.
TECHNICAL SECTION:
Components of GPU:
Now let us have a look at the components that are used in GPU:
Graphics Processors:
We can say that it’s a brain of the GPU card, it has different configurations like graphics co-processors,
all the chores related to graphic are handled by graphics co-processors. They are mostly found on highend video cards. Another configuration is graphics accelerator, in this graphics card’s chip reduce
graphics command from the CPU.
Frame Buffer:
The memory on the card is controlled by this chip, it sends information to digital to analog converter. Its
rarely used now because it does not process the image data.
Memory:
The main two kinds of memory that really live on the GPU chip are shared memory and registers. Global,
local, Constant, and Texture memory all part of a chip which all are cached.
Graphics BIOS:
A tiny ROM chip on graphics cards which have all the basic information and tell the other components
how to process by keeping relation with each other. The diagnostic tests and the input-output tests on
memory are also be performed by Bios to check the proper functionality.
Display Connectors:
Standard connectors are used by graphics cards, connectors which have video graphics array with 15
pins are mostly used by graphics cards.
GPUs Comparison:
Below we can see the performance comparison of all the cards. There is listed the profile of individual
cards. There is notably a performance gap between the GTX 1080 and Titan XP there is a huge price gap
between them but they are very close.
Video Trends:
We are living in the world of HD videos where 2/3 part of the world’s data traffic is video.
Graphics and videos both consume a noteworthy amount of memory bandwidth as the graph shown
below.
Forms of GPU:
Personnel computers pose two main forms of GPU
•
•
Integrated graphics card
Dedicated graphics cards
Dedicated Graphics Card:
These could be defined as the GPU that belongs to the most powerful class having a typical interface
integrated with a motherboard as a means of expansion slot, this is done by PCI Express or Accelerated
Graphics Port.
Integrated Graphics Card:
Integrated graphics use most of the part of computers RAM instead of using memory pf dedicated
graphics. These can be implemented on motherboards as well as on the CPU. Modern IGPs has the
capability of managing 2D and 3D graphics.
Usage specific GPU:
Different GPUs are designed for specific tasks some of them could be specified as 2D or 3D real-time
graphics.
Different uses: Gaming, cloud workstation, workstation, automated /driverless car, cloud gaming,
Artificial intelligence cloud.
Working of GPU:
In early ages when scientist performs scientific computing with GPUs, they had to map codes in the
matrix operations in order to manipulate it. This method is too large and complicated but now the
programming languages introduced which mark the GPU’s straight. A program consists of two parts one
part run on the CPU which is a host and the kernel runs on GPU. As the diagram shows the CPU part
done the data gathering and set parameters where the actual computation part done by the kernel
CONCLUSION:
From all the knowledge we can say that this is not an ordinary piece of hardware, it is an exotic product
which plays a major role in the latest technologies and artificial intelligence. GPU plays a fatal role as
today’s world depends on the 3D modeling gaming console and many more applications. By observing
the work which is now done on GPU we can come to a conclusion we can come with the more powerful
GPUs in the future.
REFERENCES:
https://computer.howstuffworks.com/graphics-card1.htm
https://nyu-cds.github.io/python-gpu/01-introduction/
https://www.lms.ac.uk/sites/lms.ac.uk/files/files/reports/GPU-KT-report-screen.pdf
https://en.wikipedia.org/wiki/Graphics_processing_unit
https://www.techopedia.com/definition/24862/graphics-processing-unit-gpu