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Rent's rule

Rent's rule is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Rent's rule rather than just read about it. In short: Rent's rule is an empirical observation about the organization of computing logic, specifically the relationship between the number of external signal connections to a logic block (i.e., the number of pins) with the number of logic gates in the logic block, and has been applied to circuits ranging from small digital circuits to mainframe computers. Put simply, it states that there is a simple power law relationship…

Rent's rule — main illustration
Rent's rule — illustration

Key takeaways

  • Rent's rule belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Rent's rule to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Rent's rule from memory before moving on to harder problems.

Reference excerpt

Rent's rule is an empirical observation about the organization of computing logic, specifically the relationship between the number of external signal connections to a logic block (i.e., the number of pins) with the number of logic gates in the logic block, and has been applied to circuits ranging from small digital circuits to mainframe computers. Put simply, it states that there is a simple power law relationship between these two values (pins and gates).

E. F. Rent's discovery and first publications In the 1960s, E. F. Rent, an IBM employee, found a remarkable trend between the number of pins (terminals, T) at the boundaries of integrated circuit designs at IBM and the number of internal components (g), such as logic gates or standard cells. On a log–log plot, these datapoints were on a straight line, implying a power-law relation T = t g p {\displaystyle T=tg^{p}} , where t and p are constants (p < 1.0, and generally 0.5 < p < 0.8). Rent's findings in IBM-internal memoranda were published in the IBM Journal of Research and Development in 2005, but the relation was described in 1971 by Landman and Russo. They performed a hierarchical circuit partitioning in such a way that at each hierarchical level (top-down) the fewest interconnections had to be cut to partition the circuit (in more or less equal parts). At each partitioning step, they noted the number of terminals and the number of components in each partition and then partitioned the sub-partitions further. They found the power-law rule applied to the resulting T versus g plot and named it Rent's rule. Rent's rule is an empirical result based on observations of existing designs, and therefore it is less applicable to the analysis of non-traditional circuit architectures. However, it provides a useful framework with which to compare similar architectures.

Theoretical basis Christie and Stroobandt later derived Rent's rule theoretically for homogeneous systems and pointed out that the amount of optimization achieved in placement is reflected by the parameter p {\displaystyle p} , the Rent exponent, which also depends on the circuit topology. In particular, values p < 1 {\displaystyle p<1} correspond to a greater fraction of short interconnects. The constant t {\displaystyle t} in Rent's rule can be viewed as the average number of terminals required by a single logic block, since T = t {\displaystyle T=t} when g = 1 {\displaystyle g=1} .

Special cases and applications Random arrangement of logic blocks typically have p = 1 {\displaystyle p=1} . Larger values are impossible, since the maximal number of terminals for any region containing g logic components in a homogeneous system is given by T = t g {\displaystyle T=tg} . Lower bounds on p depend on the interconnection topology, since it is generally impossible to make all wires short. This lower bound p ∗ {\displaystyle p*} is often called the intrinsic Rent exponent, a notion first introduced by Hagen et al. It can be used to characterize optimal placements and also measure the interconnection complexity of a circuit. Higher (intrinsic) Rent exponent values correspond to a higher topological complexity. One extreme example ( p = 0 {\displaystyle p=0} ) is a long chain of logic blocks, while a clique has p = 1 {\displaystyle p=1} . In realistic 2D circuits, p ∗ {\displaystyle p*} ranges from 0.5 for highly-regular circuits (such as SRAM) to 0.75 for random logic. System performance analysis tools such as BACPAC typically use Rent's rule to calculate expected wiring lengths and wiring demands. Rent's rule has been shown to apply among the regions of the brain of Drosophila fruit fly, using synapses instead of gates, and neurons which extend both inside and outside the region as pins.

Estimating Rent's exponent To estimate Rent's exponent, one can use top-down partitioning, as used in min-cut placement. For every partition, count the number of terminals connected to the partition and compare it to the number of logic blocks in the partition. Rent's exponent can then be found by fitting these datapoints on a log–log plot, resulting in an exponent p. For optimally partitioned circuits, p ′ = p ∗ {\displaystyle p'=p*} but this is no longer the case for practical (heuristic) partitioning approaches. For partitioning-based placement algorithms p ∗ ≤ p ′ ≤ p {\displaystyle p^{*}\leq p'\leq p} .

Region II of Rent's rule Landman and Russo found a deviation of Rent's rule near the far end, i.e., for partitions with a large number of blocks, which is known as Region II of Rent's Rule. A similar deviation also exists for small partitions and has been found by Stroobandt, who called it Region III.

… excerpt ends here. Continue reading the full article.

Illustrations

Rent's rule: Experimental data of terminals to gates on a log-log plot conforming to Rent's rule
Experimental data of terminals to gates on a log-log plot conforming to Rent's rule

Worked examples

Example 1 — a first encounter with Rent's rule

Start with the simplest possible case. Write down what Rent's rule claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Rent's rule before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Rent's rule ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Rent's rule

In research
Rent's rule appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Rent's rule in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Rent's rule is common in secondary-school and first-year university syllabi. It links to neighbouring topics Computer architecture statements, Electronic design automation, Gate arrays, so understanding it makes those chapters shorter.
In everyday life
Look for Rent's rule outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Rent's rule in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Rent's rule means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Rent's rule out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Rent's rule in simple terms?

Rent's rule is an empirical observation about the organization of computing logic, specifically the relationship between the number of external signal connections to a logic block (i.e., the number of pins) with the number of logic gates in the logic block, and has been applied to circuits ranging…

Why does Rent's rule matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Rent's rule?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Rent's rule.

Tags

  • Computer architecture statements
  • Electronic design automation
  • Gate arrays

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