In the beginning, there was the vacuum tube. And just about all the hardware based on it was what today we would call open. Early consumer electronic products, such as radios and television sets, often shipped with user manuals that contained full schematics, a list of replacement parts, and detailed instructions for servicing. Very little changed when the transistor was first introduced. Indeed, into the 1980s, computers often came with schematic diagrams of their circuit boards. The Apple II, for example, shipped with a reference manual that included a full schematic of the computer’s main board, an artifact that strongly influenced me to pursue a career in electronic design. Modern user manuals lack such depth. The most complex diagram in a recent Mac Pro user manual instructs the purchaser on how to sit at the computer: “lower back supported,” “thighs tilted slightly,” “shoulders relaxed,” and so forth. What happened? Did electronics just get too hard to service or improve? Not really. In fact, improving electronic products has become too easy—particularly for the system integrators. For decades, they have, in essence, been able to sit and wait for the ICs populating their circuit boards to get better rather than put in the hard work needed to hone their existing product designs. For example, throughout the 1990s and into the new millennium, programmers were encouraged to abandon hand-optimized assembly language in favor of cramming in more features using ever higher-level languages. Snappy performance, if it wasn’t there on release day, would come soon enough with the next generation of CPUs. You can see this effect clearly if you graph the “goodness” of electronic gadgets over the years. Pick virtually any metric—performance, feature set, whatever—and arrange your graph so that the plotted parameter doubles every 18 months following Moore’s Law. But do that on a chart with a linear vertical axis. Most diagrams depicting Moore’s Law use a logarithmic vertical scale, which flattens the curve’s sharp upward trend into a much more innocuous-looking straight line.

1. =$30
One moment please

2. By:
S.SANTHOSH
13B41A0439
A technical seminar on
UNDER THE GUIDANCE OF:
Mr. M. Ravinder
(Assoc.professor)
-Its not going to be the same anymore

4. • His prediction has proven to be accurate , in part because the law is now used in the
semiconductor industry to guide long term planning and to set the targets for research
and development
• Sources in 2005 expected it to continue until least 2015 or 2020.However,2010 update
to the international technology roadmap for semiconductors has growth slowing at the
end of 2013
Significance of Moore’ s Law

5. A perspective of development
• Moore’s Law explains why the chip in your birthday card that sings you a
song has more computing power than the Allied Forces in WWII; or why your
cell phone is more powerful than NASA was at the time of the first moon
landing.

6. Do we still need further development?

7. Deceleration of Moore’s law
• Intel changed its tick-tock cycle
• In 2004, Dennard scaling began to fail, and the computing industry was
again in a power density crisis much like the bipolar crisis.
• In 2015, the energy efficiency of logic gates continues to scale, albeit more
slowly, but the data-carrying capacity and efficiency of wire are not
improving at the same pace.

8. Reasons for the death of Moore's law
• Quantum tunneling

9. Now what?
• There are various progress options beyond moore’s law but none of them is
reliable enough.
a) Spintronics
b) Nano-photonics
c) Biological Computing (DNA Storage)
d) Quantum computing

10. Biological Computing(DNA for storage)
DNA is a very stable molecule, especially if it is stored in cold, dry, and dark
conditions. We have found woolly mammoth DNA in colder regions that has been
preserved for thousands of years.
• It is volumetric and not planar like a hard drive. One gram of DNA has stored 700
terabytes of data and could eventually store about two petabytes of data, which is
equal to about three million CDs.
• It is theoretically possible to "store at least 100 million hours of high-definition
video in about a cup of DNA."

11. The issues with DNA
• Speed: The fastest current technology can sequence (read) DNA on the order of
about 1 billion bases per hour. Synthesis (write) is even slower and more
expensive as well. This is extremely slow compared to modern storage media but
would be suitable for long term data storage. The increase in sequencing speed
actually exceeds Moore’s Law.
• Rewriting: This is essentially a write-once technology, but static data like
government and historical records could benefit from this storage option. The
speed at which DNA can be sequenced or synthesized is slow, but perhaps
someday the speed will be practical.

12. How DNA storage is done?
• First, they had to convert the digital code
of 1’s and 0’s to a genetic code of A’s,
C’s, T’s, and G’s(adenine & Thymine,
Guanine & Cystonine,)
• Then take this lowly text file and
manually construct the molecule
it represents.

13. Quantum Computing
• A quantum bit or qubit is a unit of quantum information.
• Many different physical objects can be used as qubits such as atoms, photons, or
electrons.
• Exists as a ‘0’, a ‘1’ or simultaneously as a superposition of both ‘0’ & ‘1’

14.  In Quantum Mechanics, it sometimes occurs that a
measurement of one particle will effect the state of another
particle, even though classically there is no direct interaction.
 When this happens, the state of the two particles is said to be
entangled.

15.  A quantum computer is nothing like
a classical computer in design;
transistors and diodes cannot be
used.
 A single electron trapped inside a
cage of atoms.
 When the dot is exposed to a pulse of
laser light of the right wavelength &
duration, the electron is raised to an
excited state: a second burst of laser
light causes the electron to fall back
to its ground state.
 Ex: NOT gate

16.  It is the method in which a quantum computer is able to
perform two or more computations simultaneously.
 In classical computers, parallel computing is performed
by having several processors linked together.
 In a quantum computer, a single quantum processor is
able to perform multiple computations on its own.

17. Why we are not going further then?
• Compatibility
• Scalable Manufacturability
• Complexity
• Not able to generalize it
• The new way of software approach
is needed

18. Recap
• We moved fast
• We started slowing down
• We kind of stopped at a junction of ways
• We briefly explored two of the ways
• We saw why can’t we move at the same pace in the new ways
• Moore's law is never wrong but the definition is changed by omitting
transistor from the statement

19. Burial ground of one technology would definitely be a cradle for the
other one –All we don’t know is what would be the name of new born
child.
THANK YOU
Learn more at www.rebootingcomputing.ieee.org