data dependences and hazards

1.  Explain the data dependences and hazards in detail with examples. (16)

Various types of Dependences in ILP. Data Dependence and Hazards:

To exploit instruction-level parallelism, determine which instructions can be executed in parallel. If two instructions are parallel, they can execute simultaneously in a pipeline without causing any stalls. If two instructions are dependent they are not parallel and must be executed in order.

There are three different types of dependences: data dependences (also called true data dependences), name dependences, and control dependences.

Data Dependences:

An instruction j is data dependent on instruction i if either of the following holds:

• Instruction i produces a result that may be used by instruction j, or

• Instruction j is data dependent on instruction k, and instruction k is data dependent on instruction i.

The second condition simply states that one instruction is dependent on another if there exists a chain of dependences of the first type between the two instructions. This dependence chain can be as long as the entire program.

The importance of the data dependences is that a dependence

(1) indicates the possibility of a hazard,

(2) Determines the order in which results must be calculated, and

(3) Sets an upper bound on how much parallelism can possibly be exploited.

Impact of Time, volume and commodification on Cost and Price

Cost, Price and their Trends

In the past 15 years, the use of technology improvements to achieve lower cost, as well as increased performance, has been a major theme in the computer industry.

• Price is what you sell a finished good for,
• Cost is the amount spent to produce it, including overhead.                                                         

The Impact of Time, Volume, Commodification, and Packaging
The cost of a manufactured computer component decreases over time even without major improvements in the basic implementation technology. The underlying principle that drives costs down is the learning curve manufacturing costs decrease over time. As an example of the learning curve in action, the price per megabyte of DRAM drops over the long term by 40% per year. Figure 1.5 plots the price of a new DRAM chip over its lifetime.

The Microprocessor prices also drop over time, but because they are less standardized than DRAMs, the relationship between price and cost is more complex. In a period of significant competition, price tends to track cost closely. Figure 1.6 shows processor price trends for the Pentium III.

various Technology Trends in Computer Industry

Technology Trends

The changes in the computer applications space over the last decade have dramatically changed the metrics. Desktop computers remain focused on optimizing cost-performance as measured by a single user, servers focus on availability, scalability, and throughput cost-performance, and embedded computers are driven by price and often power issues.

If an instruction set architecture is to be successful, it must be designed to survive rapid changes in computer technology. An architect must plan for technology changes that can increase the lifetime of a computer.

The following Four implementation technologies changed the computer industry:

Integrated circuit logic technology—Transistor density increases by about 35% per year, and die size increases 10% to 20% per year. The combined effect is a growth rate in transistor count on a chip of about 55% per year.

Semiconductor DRAM : Density increases by between 40% and 60% per year and Cycle time has improved very slowly, decreasing by about one-third in 10 years. Bandwidth per chip increases about twice as fast as latency decreases. In addition, changes to the DRAM interface have also improved the bandwidth.

Magnetic disk technology: it is improving more than 100% per year. Prior to 1990, density increased by about 30% per year, doubling in three years. It appears that disk technology will continue the faster density growth rate for some time to come. Access time has improved by one-third in 10 years.

Network technology—Network performance depends both on the performance of switches and on the performance of the transmission system, both latency and bandwidth can be improved, though recently bandwidth has been the primary focus. For many years, networking technology appeared to improve slowly: for example, it took about 10 years for Ethernet technology to move from 10 Mb to 100 Mb. The increased importance of networking has led to a faster rate of progress with 1 Gb Ethernet becoming available about five years after 100 Mb.

These rapidly changing technologies impact the design of a microprocessor that may, with speed and technology enhancements, have a lifetime of five or more years.

Scaling of Transistor Performance, Wires, and Power in Integrated Circuits

Integrated circuit processes are characterized by the feature size, which is decreased from 10 microns in 1971 to 0.18 microns in 2001. Since a transistor is a 2-dimensional object, the density of transistors increases quadratically with a linear decrease in feature size. The increase in transistor performance, this combination of scaling factors leads to a complex interrelationship between transistor performance and process feature size.