Introduction

Overview

• Systems knowledge is power!
  • How hardware (processors, memories, disk drives, network infrastructure) plus software (operating systems, compilers, libraries, network protocols) combine to support the execution of application programs.
  • How general-purpose software developers can best use these resources.
  • A new specialization: systems programming.

Understand how things work

• Why do I need to know this stuff?
  • Abstraction is good, but don’t forget reality
• Most CS courses emphasize abstraction
  • Abstract data types
  • Asymptotic analysis
• These abstractions have limits
  • Especially in the presence of bugs
  • Need to understand details of underlying implementations
  • Sometimes the abstract interfaces don’t provide the level of control or performance you need

Hands-on: Getting started

Log into molly and run the following commands:

• Create a directory called csc231 in your home directory using the mkdir command.
• Change into that directory using the cd command.

1
2
 
mkdir csc231
cd csc231
 

• Check that you are inside csc231 using the pwd command.
• Clone the Git repository for the class’ examples.

1
2
 
pwd
git clone https://github.com/CSC231-WCU/examples.git
 

• The git clone command will download the repository into a directory called examples inside your current directory, which is csc231.
• Run the command ls -l to confirm that examples exists.
• Change into examples using cd.
• Run ls -l to see how many subdirectories there are inside examples.

1
2
3
 
ls -l
cd examples
ls -l
 

• Change into the directory 01-intro.
• Compile and run the example code nums.c.

1
2
3
 
cd 01-intro
gcc -Wno-overflow nums.c
./a.out
 

Computer arithmetic

• Does not generate random values
  • Arithmetic operations have important mathematical properties.
• Cannot assume all usual mathematical properties.
  • Due to finiteness of representations.
  • Integer operations satisfy ring properties: commutativity, associativity, distributivity.
  • Floating point operations satisfy ordering properties: monotonicity, values of signs.
• Observation
  • Need to understand which abstractions apply in which contexts.
  • Important issues for compiler writers and application programmers.

Assembly

• You are more likely than not to never write programs in assembly.
  • Compilers take care of this for you.
• Understand assembly is key to machine-level execution model.
  • Behavior of programs in presence of bugs
    • High-level language models break down
  • Tuning program performance
    • Understand optimizations done / not done by the compiler
    • Understanding sources of program inefficiency
  • Implementing system software
    • Compiler has machine code as target
    • Operating systems must manage process state
  • Creating / ../fighting malware
    • x86 assembly is the language of choice!

Memory Matters

• Random Access Memory is an un-physical abstraction.
• Memory is not unbounded.
  • It must be allocated and managed.
  • Many applications are memory dominated.
• Memory referencing bugs are especially pernicious
  • Pernicious: having a harmful effect, especially in a gradual or subtle way.
  • Effects are distant in both time and space.
• Memory performance is not uniform.
  • Cache and virtual memory effects can greatly affect program performance.
  • Adapting program to characteristics of memory system can lead to major speed improvements

Hands-on: Memory referencing bug

• We are still inside examples\intro-01 directory from Hands-on 1.

1
2
 
gcc mem1.c
./a.out
 

Memory referencing errors

• C and C++ do not provide any memory protection
  • Out of bounds array references
  • Invalid pointer values
  • Abuses of malloc and free
• Can lead to nasty bugs
  • Whether or not bug has any effect depends on system and compiler
  • Action at a distance
    • Corrupted object logically unrelated to one being accessed
    • Effect of bug may be first observed long after it is generated
• How can I deal with this?
  • Program in Java, Ruby, Python, ML, …
  • Understand what possible interactions may occur
  • Use or develop tools to detect referencing errors (e.g. Valgrind)

Beyond asymptotic complexity

• Constant factors matter!
• Exact op count does not predict performance.
  • Possible 10:1 performance range depending on how code written (given same op count).
  • Optimizations must happen at multiple level: algorithm, data representations, procedures, and loop.
• Must understand system to optimize performance
  • How programs compiled and executed.
  • How to measure program performance and identify bottlenecks.
  • How to improve performance without destroying code modularity and generality.

Hands-on: Memory system performance

• We are still inside examples\intro-01 directory from Hands-on 1.

1
2
 
gcc mem2.c
./a.out
 

Does computer just execute arithmetic and control flow operations?

• They need to get data in and out
  • I/O system critical to program reliability and performance
• They communicate with each other over networks
  • Many system-level issues arise in presence of network
  • Concurrent operations by autonomous processes
  • Coping with unreliable media
  • Cross platform compatibility
  • Complex performance issues

Layered Services

• Direct communication between applications and hardware components are impractical due to complexity.
• Operating systems provide much-needed interfaces between applications and hardware through:
  • OS/application interface: system calls.
  • HW/SW interface: x86 standard and device drivers.
• Systems programming: develop software systems that …
  • are composed of multiple modules
  • are complex
  • meets specific requirements in aspects such as performance, security, or fault tolerance.