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# Lecture 1
## Honours Programme
- [Canvas page](https://canvas.vu.nl/courses/73125)
- Early engagement and ecellence in science
- Test your brain against a problem that **no one else solved before**
## Conceptual Map of the Course
First two lectures, we are at **1**.
1. Digita Logic
2. Digital Data
## Real world example
There is no "perfect" computer system. Building a computer system is a game of **trade-offs**. No approach is optimal generally.
_We get the luxury of a general purpose processor - CPU: BUT 35x less efficient than specialized processors_
## Big Science through An Example
Millions of sensors => good understanding of the field
## Key Technolog: Ecosystem of Federated / Geo-Distributed Datacenters
- SKA1 LOW -> COMPUTER SYSTEM
- COMPUTER SYSTEM -> 68x image quality
The computer system acts like the brain of the whole process.
- **Scientific Computer System**: process final data
- No processor can do 10b computations / second as of right now.
## How to build a LARGE computer system?
```
Novel applications often require new computer systems.
```
_To outcompete in a business sense means to **out-compute**_.
> **Answer**:
> Given an application
>
> 1. Consider candidate computing technologies
> 2. Pick the most promising technology and design around it a computer system
> 3. Analyze the desing could work.
> 4. Prototype
> **System Definition**: A system is _a set of elements or parts_ coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviours, often classified as its _function_ or _purpose_.
1. More than the sum of its parts, non-linear interactions.
2. Function may be least obvious part of the system, emergence.
3. Growth, evolution, and other complex dynamics (may) appear.
## Overview of candidates
1. Manual Labor
2. Electro-Mechanical Device
3. From Scratch, Transistor-Based
4. ???
### Option 2 - An Electro-Mechanical Device
_Only six electronic digital computers would be required to satisfy the computing needs of the United States_. - **LMAO**
- ASCC
- 1937-1944, Howard Aiken, IBM build it
- Goal: 100x faster vs hand
- Reality: only 3-5x faster (due to component failures, **introduces the need for reliability**)
- ENIAC
- 1943-1947, John Mauchly and John Presper Eckert
- First all-electronic computer
- Fully automated operation
- Performance: computation speed-up 20 hours -> 20 seconds
- Data: `1000 bits`
- Unreliable
- Power-hungry
- Difficult to program
### Option 3: Build on Digital Logic
# Basics of Digital Logic
**Digital logic**: Basics of Digital Logic -> Basic Processing Unit -> Advanced Computers
## Moore's Law (# of transistors / chip)
> Density of silicon chip (**2x every 1.5 years**)
> Rock's Law (cost to produce chips)
> <br>Cost of equipment to produce chips 2x every 4 years
### Is Moore's Law Dead?
$\log_2$ growth, curve that tends to become constant over time
## Koomey's Law
> Energy efficiency increases **2x** every 1.5 years
Every additional transistor consumes additional energy.
## For now, make transitor-based computer systems
# Making a computer system
Further design an architecture:
1. Abstract wys to read data streams, so to represent data
2. Abstract (mathematical) principles of data processing
3. Real world ways to make the abstraction work in practice
# Mushroom question
Repeat the question: "ghici ciuperca ce-i"
# Boolean algebra
$$\Large x \cdot x = x^2 = x$$
$$\Large x + x = x$$
$$\Large 0 \cdot x = 0$$
$$\Large 0 + x = x$$
$$\Large 1 \cdot x = x$$
$$\Large 1 + x = 1$$
## More $\equiv$ to logic
If $x$ is a class of objects, then
$$\Large 1-x \text{ is the complement of that class}$$
Functions that can be represented in Boolean algebra
<br>Any number of parameters:
$$\Large f(x)=f(1)\cdot x + f(0) \cdot \overline{x}$$
$$\text{where } x = \text{ a condition}$$
$$\text{where } \overline{x} = \text{ complement of } x \text{ aka } \neg x$$
This function is known as a **minterm**.
Another example of a **minterm**:
$$\large f(x, y) = f(1,1)\cdot x \cdot y + f(1, 0) \cdot x \cdot \overline{y} + f(0,1) \cdot \overline{x} \cdot y + f(0,0) \cdot \overline{x} \cdot \overline{y}$$
Example of sum of products for **INVERT**:
$$\Large f(x) = \overline{x}$$
We can also make use of **polynomials**.
### Conclusion
> We have found an algebra that works on bits, for both arithmetic & logic.
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