Eduvest � Journal
of Universal Studies Volume 4 Number 12, December, 2024 p- ISSN 2775-3735- e-ISSN 2775-3727 |
|
|
|
NEXT-GENERATION CPU ARCHITECTURES: A STUDY OF THE INFLUENCE OF
NANOMETER TECHNOLOGY ON COMPUTER PERFORMANCE |
|
Ija Sudija1, Jan everhard riwurohi2, Muhamad Masruin Masad3 Universitas Budi Luhur, Indonesia1,2,3 Email: [email protected]1, [email protected]2, [email protected]3 |
|
ABSTRACT |
|
Nanometer technology has become one
of the most significant innovations in the advancement of modern CPU
architecture, enabling substantial improvements in computational performance,
energy efficiency, and transistor density. This study examines the impact of
7nm, 5nm, and 3nm technology implementation on CPU performance under various
workload scenarios, including multitasking, graphics rendering, and
artificial intelligence-based applications. Based on a series of experimental
tests, the findings indicate that reducing transistor size directly increases
processor speed by up to 30% while reducing power consumption by 20%.
However, challenges such as heat dissipation and power leakage become more
pronounced with technology below 5nm. Several proposed solutions include the
development of more advanced cooling systems and the use of alternative
semiconductor materials, such as graphene, to mitigate power leakage. This
research provides valuable insights into the future development of CPU
architecture and its impact on the technology industry as a whole. |
|
KEYWORDS |
Nanometer technology, heat dissipation, power leakage,
semiconductor technology, graphene |
|
This work is licensed under a Creative Commons Attribution-ShareAlike
4.0 International |
INTRODUCTION
����������� The
development of semiconductor technology has become the main driver of innovation in the world of
computing (Batra et al., 2019). As the demand
for faster and more efficient processor performance increases, the tech
industry has focused on developing more powerful and
energy-efficient CPU architectures
(D. Li et al., 2016). One of the
biggest innovations in recent decades has been the shift to nanometer
technology in CPU manufacturing, which has allowed chipmakers such as Intel,
AMD, and TSMC to fit more transistors into smaller spaces, resulting in faster,
more efficient, and more energy-efficient processors.
����������� Nanometer
technology refers to the physical size of the transistors used in CPU chips (Liu et al., 2020). A transistor is
a fundamental element of an electronic circuit, and by reducing the size of the
transistor to the nanometer scale, more transistors can be placed in the same area, leading to improved processor
performance (Das et al., 2021). However,
miniaturizing transistors to sizes below 7nm not only brings benefits, but also
raises a number of technical challenges, especially related
to heat dissipation
and power leakage (Radamson et al., 2020). Heat dissipation
problems arise when more transistors in a smaller space produce
more heat that must be
dissipated (He et al., 2021). Whereas power
leakage occurs when unwanted electric current flows through the transistor, which increases power consumption and decreases efficiency
(Prasad & Rim, 2022).
����������� Advances
in nanometer technology are particularly relevant in a variety of applications,
such as artificial intelligence (AI), data centers, and mobile
devices (Gill et al., 2022). The gaming
industry, for example, requires CPUs with high graphics performance and low
latency, while data center applications require CPUs that are energy-efficient but still have high
multitasking capabilities (Alam et al., 2024; Tong, 2024). In the mobile
sector, the demand for smaller, more efficient devices is increasing, which
makes nanometer technology one of the
main focuses in processor development (Atabaki et al., 2018; Miraz et al., 2018).
����������� This
study aims to analyze the influence of nanometer technology on CPU performance,
focusing on 7nm, 5nm, and
3nm technologies (Radamson et al., 2020; Sherazi et al., 2016). In addition, we
examine the challenges of heat dissipation and power leakage, as well as
innovative solutions that can be applied in the design of next-generation
CPU architectures (Z. Li et al., 2024; Zhang et al., 2023).
����������� The
development of semiconductor technology has
become a major motor in driving innovation
in the computing world (Băjenescu, 2022). As the demand
for faster and more efficient processors increases, the tech industry is
increasingly focusing on developing more powerful and
energy-efficient CPU architectures
(Haj-Yahya et al., 2018). One of the
biggest breakthroughs in recent decades has been the application of nanometer
technology in CPU production, which has allowed manufacturers such as Intel,
AMD, and TSMC to embed more transistors into smaller spaces
(Kotasthane & Manchi, 2023). As a result, the
resulting processor becomes faster,
more efficient, and more energy-efficient
(Hackenberg et al., 2015).
����������� Nanometer
technology refers to the physical size of the transistors used in CPU chips (Liu et al., 2020). By reducing the
size of the transistor to the nanometer scale, more transistors can be placed
in the same space, which directly improves
the performance of the processor
(Salahuddin et al., 2018). Although
miniaturization of transistors down to 7nm brings significant advantages, the
process also presents a variety of technical challenges, particularly related
to heat dissipation and power leakage. Heat dissipation problems arise when
more transistors in a tight space generate more heat, while power leakage
occurs when unwanted electrical current flows through the transistor, leading
to increased power consumption and decreased efficiency.
����������� Advances
in nanometer technology play a huge role in various applications, such as
artificial intelligence (AI), data centers, and mobile devices. For example,
the gaming industry requires CPUs with high graphics capabilities and low
latency, while data centers require CPUs that are energy-efficient but still
have reliable multitasking capabilities. In the mobile sector, the demand for
smaller and more efficient devices is increasing, making nanometer technology
one of the main focuses in processor development.
����������� This
study aims to examine the impact of nanometer technology on CPU performance,
with a focus on 7nm, 5nm, and 3nm technologies. In addition, the study will
also address the challenges of heat dissipation and power leakage and explore
innovative solutions that can be applied in next-generation CPU architecture
designs. )
RESEARCH METHOD
This study uses a
quantitative approach with experimental methods to measure the impact of
nanometer technology on CPU performance in various scenarios. (describe the
meaning and procedure of the method accompanied by citations) The CPU samples
used in the study include 10nm, 7nm, 5nm, and 3nm-based processors manufactured
by Intel, AMD, and TSMC. Testing is carried out in a controlled laboratory
environment to ensure consistency of results.
Testing Stage:
1.
CPU Sample Selection: We
use four generations of CPUs from different manufacturers, each with different
fabrication technologies: 10nm, 7nm, 5nm, and 3nm.
2.
Performance Testing:
Performance testing is conducted using Cinebench R23 and Geekbench 5 benchmark
software, which is designed to measure the performance of single-core and
multi-core CPUs. We also did multitasking testing using graphics rendering
applications like Blender and big data processing using Hadoop.
3.
Power Consumption
Testing: Power consumption is measured in three conditions: idle (no workload),
moderate load (e.g. video playback or light applications), and heavy load
(large graphics or simulation processing). Measurements are made using a power
meter capable of recording changes in power consumption in real-time during
testing.
4.
Operating Temperature
Testing: The operating temperature of the CPU is measured using thermal sensors
mounted on the heat sink and surface of the CPU. The test was carried out under
two conditions: idle and full load, using a standard cooling system (fan) and a
liquid cooling system.
5.
Power Leakage Analysis:
We use power leakage analysis to measure how much energy is lost through a
dormant transistor. This is done by using simulation software to simulate
intense workloads.
RESULT AND DISCUSSION
The test results
show that 7nm technology provides a significant performance improvement
compared to 10nm technology. In the Cinebench R23 test, the 7nm-based CPU
scored a single-core score of 1500 points, while the 10nm CPU only reached 1300
points. The 7nm CPU's multi-core score also shows a 25% improvement compared to
10nm, reflecting better multitasking capabilities.
At 5nm technology,
CPU performance improves even further. The multi-core score reaches 17,500
points, while power consumption is reduced by up to 20% compared to 7nm CPUs.
This shows that 5nm technology is more efficient in terms of performance and
power, which is particularly relevant for data center and cloud computing
applications. However, in 3nm technology, despite a 30% increase in performance
compared to 5nm technology, the CPU's operating temperature increases
significantly. In full-load testing, 3nm-based CPUs achieved an operating
temperature of 80�C, 8�C higher than 5nm CPUs, which indicates greater heat
dissipation challenges. Power leakage is also increasing in this technology.
(Accompany with pictures/tables if available as research evidence)
Discussion
The results of
this study provide clear insights into the influence of nanometer technology on
CPU performance. In general, reducing the size of the transistor from 10nm to
3nm results in significant improvements in computing performance, especially in
tasks that require parallel execution and graphics processing. This increase is
especially important in sectors such as gaming, artificial intelligence (AI),
and data centers that require high computing power. In Cinebench R23 and
Geekbench 5 tests, 5nm and 3nm-based CPUs showed much better multitasking
capabilities compared to 7nm and 10nm-based CPUs, confirming the positive
impact of transistor miniaturization.
However, this
performance improvement comes with technical challenges that must be overcome.
One of the main challenges found is heat dissipation in 3nm-based CPUs.
Although 3nm technology delivers the best performance in multi-core tests,
higher operating temperatures indicate that standard cooling systems (fans) may
no longer be sufficient to maintain the thermal stability of the CPU under
heavy loads. Therefore, solutions such as liquid cooling systems or
phase-change cooling need to be considered to maintain the CPU temperature
within safe limits. This increase in heat dissipation is mainly due to the
increasing density of transistors, which results in more heat energy to expend.
In addition to
heat dissipation, power leakage is another challenge in technologies below 5nm.
3nm-based CPUs show a 7% increase in power leakage compared to 5nm-based CPUs.
This happens because the smaller distance between the transistors causes
unwanted electrical current to flow through the inactive transistor, increasing
overall power consumption. This power leakage is a serious problem in the
context of data center applications that require high energy efficiency to
manage thousands of servers simultaneously.
To address this
issue, recent research suggests that the use of alternative semiconductor
materials such as graphene and carbon nanotubes can help reduce power leakage.
This material has better thermal conductivity than silicon, which can help
solve the problems of heat dissipation and power leakage in nanometer
technology below 5nm. In addition, more advanced FinFET and GAAFET technologies
are also being developed to reduce the effects of power leakage without
sacrificing performance.
Although 3nm
technology offers significant performance improvements, its mass adoption still
requires further development in terms of cooling technology and semiconductor
materials. Heterogeneous architectural solutions, such as those implemented by
Apple in 5nm-based M1 processors, could be a model for future CPU development.
This architecture combines high-performance cores and power-efficient cores to
improve multitasking performance while minimizing power consumption on lighter
tasks.
Overall, the
development of nanometer technology is an important step in the evolution of
CPU architecture, but the problems of heat dissipation and power leakage must
be addressed to ensure the stability and efficiency of next-generation CPUs.
CONCLUSION
����������� Nanometer
technology (already) brings many advantages in the development of CPU
architectures, including improved performance, energy efficiency, and
multitasking capabilities. The study showed that reducing the size of the
transistor from 10nm to 3nm provided a (significant) increase in computing
performance, with 3nm-based CPUs providing the best performance in multi-core
testing. However, heat dissipation and power leakage are technical challenges
that must be overcome, especially in technologies below 5nm.
����������� To ensure the
success of next-generation nanometer technology, further developments in
cooling technology and semiconductor materials are needed. Materials such as
graphene and liquid cooling technology offer a promising solution to this
problem. Additionally, the adoption of heterogeneous CPU architectures can help
improve performance and energy efficiency, especially in applications that
require high computing power such as AI and data centers.
����������� More research is
needed to explore how heat dissipation can be optimized on 3nm-based CPUs or smaller.
The future of the semiconductor industry relies heavily on innovations in
materials and cooling technologies to maximize the potential of nanometer
technology below 5nm.
REFERENCES
Alam, S., Yakopcic, C., Wu, Q., Barnell, M., Khan, S., & Taha, T. M.
(2024). Survey of deep learning accelerators for edge and emerging computing. Electronics,
13(15), 2988.
Atabaki, A. H., Moazeni, S., Pavanello, F., Gevorgyan, H.,
Notaros, J., Alloatti, L., Wade, M. T., Sun, C., Kruger, S. A., & Meng, H.
(2018). Integrating photonics with silicon nanoelectronics for the next
generation of systems on a chip. Nature, 556(7701), 349�354.
Băjenescu, T.-M. I. (2022). Electronics: The Innovation
Driver of the Automotive Industry. Electrotehnica, Electronica, Automatica,
70(1).
Batra, G., Jacobson, Z., Madhav, S., Queirolo, A., &
Santhanam, N. (2019). Artificial-intelligence hardware: New opportunities for
semiconductor companies. McKinsey and Company, 2.
Das, S., Sebastian, A., Pop, E., McClellan, C. J., Franklin,
A. D., Grasser, T., Knobloch, T., Illarionov, Y., Penumatcha, A. V, &
Appenzeller, J. (2021). Transistors based on two-dimensional materials for
future integrated circuits. Nature Electronics, 4(11), 786�799.
Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R.,
Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., & Abraham, A. (2022). AI
for next generation computing: Emerging trends and future directions. Internet
of Things, 19, 100514.
Hackenberg, D., Sch�ne, R., Ilsche, T., Molka, D., Schuchart,
J., & Geyer, R. (2015). An energy efficiency feature survey of the intel
haswell processor. 2015 IEEE International Parallel and Distributed
Processing Symposium Workshop, 896�904.
Haj-Yahya, J., Mendelson, A., Asher, Y. Ben, &
Chattopadhyay, A. (2018). Energy efficient high performance processors:
recent approaches for designing green high performance computing. Springer.
He, Z., Yan, Y., & Zhang, Z. (2021). Thermal management
and temperature uniformity enhancement of electronic devices by micro heat
sinks: A review. Energy, 216, 119223.
Kotasthane, P., & Manchi, A. (2023). When the Chips
Are Down: A Deep Dive into a Global Crisis. Bloomsbury Publishing.
Li, D., Chen, X., Becchi, M., & Zong, Z. (2016).
Evaluating the energy efficiency of deep convolutional neural networks on CPUs
and GPUs. 2016 IEEE International Conferences on Big Data and Cloud
Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable
Computing and Communications (SustainCom)(BDCloud-SocialCom-SustainCom),
477�484.
Li, Z., Luo, H., Jiang, Y., Liu, H., Xu, L., Cao, K., Wu, H.,
Gao, P., & Liu, H. (2024). Comprehensive review and future prospects on
chip-scale thermal management: Core of data center�s thermal management. Applied
Thermal Engineering, 123612.
Liu, C., Chen, H., Wang, S., Liu, Q., Jiang, Y.-G., Zhang, D.
W., Liu, M., & Zhou, P. (2020). Two-dimensional materials for
next-generation computing technologies. Nature Nanotechnology, 15(7),
545�557.
Miraz, M. H., Ali, M., Excell, P. S., & Picking, R.
(2018). Internet of nano-things, things and everything: future growth trends. Future
Internet, 10(8), 68.
Prasad, C. V., & Rim, Y. S. (2022). Review on interface
engineering of low leakage current and on-resistance for high-efficiency
Ga2O3-based power devices. Materials Today Physics, 27, 100777.
Radamson, H. H., Zhu, H., Wu, Z., He, X., Lin, H., Liu, J.,
Xiang, J., Kong, Z., Xiong, W., & Li, J. (2020). State of the art and
future perspectives in advanced CMOS technology. Nanomaterials, 10(8),
1555.
Salahuddin, S., Ni, K., & Datta, S. (2018). The era of
hyper-scaling in electronics. Nature Electronics, 1(8), 442�450.
Sherazi, S. M. Y., Chava, B., Debacker, P., Bardon, M. G.,
Schuddinck, P., Firouzi, F., Raghavan, P., Mercha, A., Verkest, D., &
Ryckaert, J. (2016). Architectural strategies in standard-cell design for the 7
nm and beyond technology node. Journal of Micro/Nanolithography, MEMS, and
MOEMS, 15(1), 13507.
Tong, A. (2024). The Evolution of AI Engineering: Hardware
and Software Dynamics, Historical Progression, Innovations, and Impact on
Next-Generation AI Systems. Library Progress International, 44(3),
19715�19737.
Zhang, Y., Shan, K., Li, X., Li, H., & Wang, S. (2023).
Research and Technologies for next-generation high-temperature data
centers�State-of-the-arts and future perspectives. Renewable and Sustainable
Energy Reviews, 171, 112991.