# Integer Representations and Counting in the Bit Probe Model - PowerPoint PPT Presentation

Integer Representations and Counting in the Bit Probe Model

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## Integer Representations and Counting in the Bit Probe Model

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1. Integer Representations and Counting in the Bit Probe Model M. Zaiur Rahman and J. Ian Munro Cheriton School of Computer Science University of Waterloo Waterloo On Canada

2. Integer Representations • Standard: n bits representing {0..2n} • # bits … optimal • Increment: • Θ(n) bit inspections/changes worst case • O(1) amortized, but not if we include decrement

3. Redundant Binary Numbers • Use “digits” 0,1,2 but representation is in binary, 2 is a delayed carry e.g. 01220 = 10100 • Space 2n bits (or reduce to about (lg 3) n) • Increment O(1), as we de-amortize the scan to release the rightmost carry • Decrement is tricky, easiest to use digit “-1” • Note the extra lg n bits for the scan pointer

4. Gray Codes.. Due to Gray..of course Binary Reflected Gray Code (BRGC) • Of dimension n (i.e. n bits, numbers [0..2n] • A sequence of 2n strings each of length n G(n) = 0.G(n-1), 1.G(n-1)R (reversal is on thesequence order, not the individual codes)

5. Increment on a Gray Code • Even parity: flip rightmost 1 bit

6. Increment on a Gray Code • Even parity: flip rightmost bit 00110000 → 00110001

7. Increment on a Gray Code • Even parity: flip rightmost bit 00110000 → 00110001 • Odd parity: flip the bit to left of rightmost 1 01110000 → 01010000

8. Increment on a Gray Code • Even parity: flip rightmost bit 00110000 → 00110001 • Odd parity: flip the bit to left of rightmost 1 01110000 → 01010000 • Costs:1 bit changed, n inspections (worst case) • Or: add parity bit, O(1) amortized insert, 2 bits changed • Integrate parity bit with code (no extra bit [Lucal])

9. Our First Result: Lower Bound Theorem: Any representation of [0..2n] using exactly n bits requires Ω(√n) bit inspections in the worst case. Proof: Model, apply Sunflower Lemma and manipulate

10. Sunflower Lemma [Ёrdos & Rado] • Sunflower with p petals • Sets S1, …, Sp so SiSj is same for all i,j Lemma: S1, …, Sp is a system of sets each of size at most q. If m>(p-1)q+1q!, then it contains a subcollection with p petals Use the lemma with m as small as possible

11. Back to Algorithms • We want a scheme that balances (as well as possible) • Bit changes • Bit inspections • Extra bits Lower bound says no extra bits  lots of inspections

12. The increment in BRGC • Key issue … that rightmost 1 Lemma: On increment or decrement, the position of rightmost 1 in any segment of the leftmost bits changes only when that bit is flipped, except for the case of leftmost bit going 1→0 on increment (or 0 → 1 on decrement)

13. De-amortizing • The lemma lets us de-amortize: as with redundant binary representation. With some details: Theorem: There is a representation using n + lg n + 3 bits (a pointer is in there), requiring 2 lg n +4 bit inspections and 4 bit changes for increment or decrement.

14. Moving Along • Complicating issue:Mixing increments and decrements forces us to add flags • (for {inc, dec} and {done yet , not done} • Idea: use the lower order lg n bits to give the pointer into the leftmost n - lg n bits • This would seem to require a table (or model issue) to translate

15. But • Permute the code of the leading n – lg n bits and use trailing bits directly to walk through them in “code order” • Indeed, we don’t need n – lg n to be a power of 2 Theorem: There is a representation using n + 3 bits, requiring lg n + 6 bit inspections and 7 bit changes for increment or decrement.

16. Addition and Subtraction • Adding or subtracting and m digit (standard notation) integer to update an n digit integer (n > m): • n + O(lg2n) bits, • O(m + lg n) inspections/changes

17. Open Issues • Improve the lower bound to n bits inspected in no extra bits • Lower bound trading off bits changed with space and bits inspected • Tweaking upper bounds