September 10, 2003Serguei A. Mokhov, 1 Introduction SOEN228 Revision 1.1 September 10, 2003

Serguei A. Mokhov, 2 Contents Me, Myself, and I Lecture 1 Exercises review Assignment 1 Theory review Von Neumann Model

September 10, 2003Serguei A. Mokhov, 3 Me, Myself, and I Name: Serguei Mokhov; it is okay to call me just Serguei; prefixes such as “Sir”, “Professor” and alike are NOT part of my name :-) The best way to reach me is by

September 10, 2003Serguei A. Mokhov, 4 Exercise (1) You are given a class list that shows the university ID, name, addresses of each student enrolled in SOEN228. Write a human program that you can execute that systematically extract a sublist of students whose first name is Pierre. These students should be listed in ascending order of their ID. Give an incorrect solution that the human program should not generate.

September 10, 2003Serguei A. Mokhov, 5 Exercise (2) Show a sequence of state changes in executing your human program by showing all changes to the extracted sublist and the control pointer, up to and including processing of the first two entries of the given list. Assume both entries contain Pierre as the first name.

September 10, 2003Serguei A. Mokhov, 6 Exercise (3) Describe an example use of principle of locality in everyday life of yours that helps you to achieve better ‘performance’. Repeat the same in your experience in using the internet.

September 10, 2003Serguei A. Mokhov, 7 Exercises Suppose the area of a chip does not change in a decade but the number of transistors in a chip can double every 2 years. Suppose also that the current technology allows you to put 10 million transistors in a chip. How many transistors can be put in a chip 10 years later? Explain the implication of this technology curve on the capacity of a memory chip and the capability of a processor chip.

September 10, 2003Serguei A. Mokhov, 8 Three Basic Principles in System Design Locality Concurrency Atomicity

September 10, 2003Serguei A. Mokhov, 9 Locality Locality of information (data or program) to a processor reduces the latency (waiting time) and hence improves performance (speed, response time, time to solution). Examples that you will learn in this course include: –Registers inside a processor that a programmer can use to store (buffer) program variables temporally. –Cache memory that automatically buffers information stored in main memory (RAM). –Main memory that buffers information stored in disk Locality issues matter a lot in parallel computing (advanced topic if we have time).

September 10, 2003Serguei A. Mokhov, 10 Concurrency Operations can be performed in parallel when the outcome is as if they are performed in sequence according to the order they appear in a program. Hence concurrency improves system speed. Examples: –Concurrent transfers between different pairs of registers implement concurrent data-paths, leading to a faster instruction cycle (the duration for fetching and executing a program instruction). –Computation and input/output can be carried out concurrently whenever the processor is not needed in the latter.

September 10, 2003Serguei A. Mokhov, 11 Atomicity Information accesses should be serializable, i.e., the results are as if they have occurred in some serial ordering. Hence when a writer and a reader may overlap in their accesses, then the system must ensure that the end result is as if they have occurred in some temporal order. In some cases, the ordering is intended, and in some others, the it is not. (Related: Synchronization) Examples: –The computer (CPU) should not write into the printer buffer until the previous line stored in the buffer has already been printed. –System bus design ensures the atomicity of a bus transaction between a master and a slave connected to the bus.

September 10, 2003Serguei A. Mokhov, 12 Von Neumann Model A program formed of instructions and data is stored in memory; CPU fetches and executes instructions from the memory (sequentially). Being dropped in parallel computing Logical View of A Von Neumann Computer Model (see next slide)

September 10, 2003Serguei A. Mokhov, 13 Logical View of A Von Neumann Computer Model Memory Unit Arithmetic and Logic Unit Control Unit Output Unit Input Unit

September 10, 2003Serguei A. Mokhov, 14 Von Neumann Model Explained (1) Arithmetic and Logic Unit (ALU): –Performs arithmetical and logical operations Control Unit (CU): –Issues control signals to other units to do what and when ALU + CU = CPU, Central Processing Unit –A.k.a Processor

September 10, 2003Serguei A. Mokhov, 15 Von Neumann Model Explained (2) Memory Unit (MU) –Stores your program and its data; consists of distinct locations (like mailboxes) with distinct addresses, say from 0 to 2 30 Input Unit (IU) –Enables the CPU to receive input data from the external word (e.g. keyboard, mouse, CD-ROM) Output Unit (OU) –Accepts output from processor or memory and passes it on to the external world; (e.g. monitor, printer)

September 10, 2003Serguei A. Mokhov, 16 Logical View of A Von Neumann Computer Model (2) Memory Unit CPU Output Unit Input Unit KeyboardMouseMonitorPrinter