Analysis of Moore's Law, Cache Memory, and the Internet of Things

Desklib provides past papers and solved assignments for students. This report explores computer architecture, including Moore's Law, cache memory, and the Internet of Things.

Part A
A-1 Discuss Moore’s law in detail and analyze how it affects you. In your answer, you must have
one graph and one table.
Moore’s law stated that in every two years the number of transistors in integrated circuits and
overall power and speed of processing increases. The guidelines are quite considerable but this law
is not much common. For the least component cost, the complexity is increased uninterruptedly at
the rate of the factor of two. Moore manifested his law for the degree of growth of the numeral of
the transistors on the integrated chip [1].

Moore’s law impact on technology:
After the projection of the law, it used to fixed goals and begin the road maps and achieve
acceptance in the industries. After some years of Moore’s prediction, the ICs production became
more sophisticated besides concerning the multi-layered exertions by different particular
companies. This law impacted the technology in a positive manner. Therefore, to set the specific
targets measures are required to be set in place. One more impact is that the computing devices
continuously show the exponential growth in the convolution and power of computing and for the
creator and the clients, there is analogous decrement occur in the cost. This law gives a positive
impact on the electric apparatus particular for the digital systems in general and the computers in
particular. Its impact is also shown in cloud computing in which there is a straight request for more
components and it also shows the movement in the technology from microelectronics to the
Nanoelectronics [2].
A-2 Research on the associative mapping of cache with the memory. Explain your understanding
with a help of a suitable diagram.
Cache memory is referred as the high-speed memory which is commonly used to increase the
rapidity of the program by implementing the recent program and data which is offered to the CPU at
a fast frequency. In comparison with the main memory, cache memory has less amount of access
time. A check is ready to find out that if the word is in the cache then CPU tries to read memory from
the main memory. The principle of locality of reference refers as the slab of main memory have
some different word along with the word if the word is not there then the mandatory word is sent to
the CPU. There are some auxiliary strategies like FIFO, LFU, etc., are used when there is no vacant
slabs find in the cache. Cache is generally planned to be a user-transparent to discover an article in
the cache [3].

This memory operation depends basically on the several features like operations of cache, aspects of
design, and the bandwidth of the cache.
Mainly, the cache memory has the three techniques:
1. Direct mapping:
It depends on the concept that if the jth block of memory has to be replaced by the ith block
of the main memory.
2. Associative mapping:
This technique is commonly used to avoid the high-level clash slip, any block of the main
memory can be engaged in the cache memory.
3. Set-associative mapping:
This technique is designed to come out from the huge tag comparisons and a huge level of
clash slip in the associative mapping and in the direct mapping technique respectively [4].
Part B
B-Q1 From digital logic circuit given below construct the truth table as specified on the table.

A B C D D’ AB C+D’ CD’ X
0 0 0 0 1 0 1 0 1
0 0 0 1 0 0 0 0 0
0 0 1 0 1 0 1 1 1
0 0 1 1 0 0 1 0 1
0 1 0 0 1 0 1 0 1
0 1 0 1 0 0 0 0 0
0 1 1 0 1 0 1 1 1
0 1 1 1 0 0 1 0 1
1 0 0 0 1 0 1 0 1
1 0 0 1 0 0 0 0 0
1 0 1 0 1 0 1 1 1
1 0 1 1 0 0 1 0 1
1 1 0 0 1 1 1 0 1
1 1 0 1 0 1 0 0 1
1 1 1 0 1 1 1 1 1
1 1 1 1 0 1 1 0 1
B-Q2 Discuss in detail IEEE-754 32-bit Single-Precision Floating-Point Numbers with an example.
IEEE-754, single precision floating point number is defined as the binary computing arrangement
which has 4 bytes in the computer memory. Binary 32 is generally the 32-bit base 2 format.it has
some standard specifics that is: [5]
Sign bit: 1 bit
Exponent width: 8 bits
Significant precision: 24
Example:
Consider some floating number presented in the IEEE single precision as
01101011101101010000000000000000. Conclude the sign σ, exponent e, and conclude the value of
x=σ⋅x¯⋅2e.

The first bit of the number given is b1=0. It tracks the sign of x is σ==+1.
Similarly, the next bits are 11010111 of b2b3…….b9 and E can be written as
E=e+127
Now we find out that which decimal number concludes the binary number E=(11010111)2
Now we have
E=1+2+4+0+16+0+64+128=215
So the value of e is e=E-127= 215-127=88
Now for finding mantissa part, considering the remaining 23 bits that is b10b11b12…b32.
Finally, the decimal representation of the number is x= σ. x¯⋅2e=+ (1.4140625)*288 [6]
a. Normalized form
The floating point can be said to be normalized when the integer part of the mantissa in floating
point is forced to exactly 1 (significant digit) but allow the fractional part of mantissa to be whatever.
This will maximize the precision for the given number of bits.
Taking an example of decimal number 172.625. The relative binary number of this decimal number
will be 10101100.101 with base 2. Now, for normalizing this number
10101100.101*(2^0)
1010110.0101*(2^1)
101011.00101*(2^2)
10101.100101*(2^3)
1010.1100101*(2^4)
101.01100101*(2^5)
10.101100101*(2^6)
1.0101100101*(2^7). Hence, in this number, the integer part is forced to be 1. So,
1.0101100101*(2^7) is the normalized form for 172.625 decimal number. However, for increasing
the efficiency, in binary number representation, integer part 1 is just pretended. Only, the fractional
part of mantissa will be recommended [7].
b. De-normalization form
In de-normalized form, the exponent is all 0’s, which is assumed to be leading 0 before the binary
point. The de-normalized number can be represented as (-1)s * 0.f *2-126, where, s is for sign bit and f
is the fraction in floating number. Considering an example,

Trying to write 121.25 and then encoding it as 1212500 -04. This is the process of normalizing. In this
case, the two lower case digits become zero. But expressing this value as 0121250 -03 or 0012125 -
02 equivalently can be termed as de-normalizing terms.
B-Q3.
In this unit, we have discussed about Moore laws and how these laws are helpful for the industrial
field on making integrated IC’s by using less number of transistors as per reduction of logic gates.
After the Moore prediction, how IC production extended to a vast scale. Also, we have discussed
about the transistors used in the processors in these integrated circuits.
After this, coming to computer organization, the memory types and dependence of them have been
discussed. Cache memory, dynamic memory and main memory and how CPU interacts with these
memories and the mechanism, all have been discussed here. In cache memory, the techniques for
mapping of them have also been discussed.
After this, the logic circuit and the float point numbers from IEEE 754 have been discussed and also
how the normalized and de-normalized form have been created.
After this much of study, the report have been ended by the topic of internet of things which is a
well-defined technology in present era. The challenges and problems of the world and how by
introducing internet of things in the scenario, these challenges have been tackled, all are discussed
in this assessment.
Feedback- This unit is so much interesting, that I have learnt a more about the principle of
production of IC’s in industries. How digital electronics have been implemented and how internet of
things is trending and solving the current challenges and problems of current scenario. A proper
guidance have been given to me in this unit.
Part C
INTERNET OF THINGS
Internet of things is defined as the network of the computing devices which are used in general day
to day operations like home appliances which can be able to interact and exchange data between
each other. Before the internet of things is introduced, there were many challenges and problems
faced by the world. As because of the ageing population, there was considerable pressure on health
care sectors for providing convenient and cost-effective treatment to the population. One of the
major challenge faced by the world until now is global warming and undesirable climatic change.
Thus internet of things helps to analyze the real-time data for monitoring the climatic changes and
ensure us to get safety measures. The challenges faced by the world in improving and development
of cities, convenient and smart transportation system, in the agriculture sector for food and water,
smart home appliances, etc. all can be resolved by the internet of things [8].

Internet of things have applications in many of the sectors like for solving the problem of non-
renewable resources and conserving the energy by smart home appliances which consumes less
energy, smart streetlights etc. In the agriculture sector also, automating irrigation practices through
the internet of things serves best to the farmers by reducing their efforts and improving their
productivity by monitoring the crop fields through sensors. In communication and computer science,
the internet of things has grown to an extent ensuring proper communication technologies through
internet [9].
Outcomes:
Some of the major outcomes of the internet of things are in the communication sector, automation
fields, information technology, comfort, business and solving many global challenges also. In
machine to machine communication by providing every system a base of the internet is provided by
IOT and hence making the efficiency of the systems to be increased [1]. Without any human
interference, the wireless infrastructure of smart devices operated on its own through the internet.
In health care sectors by providing a digital platform to monitor patient’s at their homes,
implementing chips in patients for vital signs and many more, all are provided by the internet of
things. In the business field also, by monitoring the consumer trends, great sales can be achieved
which in return leads to great revenues and profits.

REFERENCES
[1]D. MITCHELL, "What is Moore's Law & How Does it Affect the Pcs That You Use?", Rack Simply,
2018. [Online]. Available: https://racksimply.com/what-is-moores-law/. [Accessed: 18- Jan- 2019].

[2]T. Sieber, "What Is Moore’s Law, And What Does It Have To Do With You? [MakeUseOf
Explains]", MakeUseOf, 2012. [Online]. Available: https://www.makeuseof.com/tag/what-is-moores-
law-and-what-does-it-have-to-do-with-you-makeuseof-explains/. [Accessed: 18- Jan- 2019].
[3]E. technique., "Explain Cache Memory and describe Cache mapping technique.", Ques10.com,
2019. [Online]. Available: http://www.ques10.com/p/11169/explain-cache-memory-and-describe-
cache-mapping--1/. [Accessed: 18- Jan- 2019].
[4]D. Das, "Cache Memory Mapping Techniques with Diagram and Example", CSETutor. [Online].
Available: https://www.csetutor.com/cache-memory-mapping-techniques-examples/. [Accessed:
18- Jan- 2019].
[5]"IEEE Single Precision Floating Point Format Examples 1 - Mathonline", Mathonline.wikidot.com.
[Online]. Available: http://mathonline.wikidot.com/ieee-single-precision-floating-point-format-
examples-1. [Accessed: 18- Jan- 2019].
[6]Cse.hcmut.edu.vn. [Online]. Available:
http://www.cse.hcmut.edu.vn/~hungnq/courses/501120/docthem/Single%20precision%20floating-
point%20format%20-%20Wikipedia.pdf. [Accessed: 18- Jan- 2019].
[7]D. Rankin and E. Chris, "How to normalize a mantissa", Stack Overflow, 2015. [Online]. Available:
https://stackoverflow.com/questions/28800565/how-to-normalize-a-mantissa#. [Accessed: 18- Jan-
2019].
[8]"Discover the Advantage of IOT system", Odyseed, 2019. [Online]. Available:
https://odyseed.com/advantages-iot-system/?lang=en. [Accessed: 18- Jan- 2019].
[9]S. Ranger, "What is the IoT? Everything you need to know about the Internet of Things right now |
ZDNet", ZDNet, 2018. [Online]. Available: https://www.zdnet.com/article/what-is-the-internet-of-
things-everything-you-need-to-know-about-the-iot-right-now/. [Accessed: 18- Jan- 2019].