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Simultaneous Multiparty Communication Protocols for Composed - - PowerPoint PPT Presentation

Simultaneous Multiparty Communication Protocols for Composed Functions Yassine Hamoudi IRIF , Universit Paris Diderot, CNRS MFCS 2018 Number-On-Forehead model [Chandra, Furst, Lipton83] 2 F : X 1 X k {0,1} Player 1 Player


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SLIDE 1

Simultaneous Multiparty Communication Protocols for Composed Functions

Yassine Hamoudi IRIF , Université Paris Diderot, CNRS MFCS 2018

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SLIDE 2

Number-On-Forehead model [Chandra, Furst, Lipton’83]

2

F(x1, x2, x3, x4) = ?

x2, x3, x4 x1, x3, x4 x1, x2, x3 x1, x2, x4

Player 1 Player 2 Player 4 Player 3

F : X1 × ⋯ × Xk → {0,1}

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SLIDE 3

Number-On-Forehead model [Chandra, Furst, Lipton’83]

2

  • Player i doesn’t know (⇔ Number-On-Forehead)
  • Communicate by broadcasting bits
  • Players have unlimited computational power

xi

F(x1, x2, x3, x4) = ?

x2, x3, x4 x1, x3, x4 x1, x2, x3 x1, x2, x4

Player 1 Player 2 Player 4 Player 3

F : X1 × ⋯ × Xk → {0,1}

N

  • r

a n d

  • m

n e s s i n t h i s t a l k

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SLIDE 4

Examples

3

  • Player 1 sends x2
  • Player 2 sends F(x1,…, xk)

An always-O(n) protocol: F is easy / protocol is efficient ⇔ communication cost logO(1)(n) x1, …, xn ∈ {0, 1}n

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SLIDE 5

Examples

3

Equality: x1 = … = xk? Two players: Ω(n) k ≥ 3 players: O(1)

  • Player 1 indicates if x2 = … = xk
  • Player 2 indicates if x1 = x3
  • Player 1 sends x2
  • Player 2 sends F(x1,…, xk)

An always-O(n) protocol: F is easy / protocol is efficient ⇔ communication cost logO(1)(n) x1, …, xn ∈ {0, 1}n

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SLIDE 6

Applications of the NOF model

4

  • Branching programs, Ramsey theory [Chandra, Furst, Lipton'83]
  • Quasi-random graphs [Chung, Tetali'93]
  • Proof complexity [Beame, Pitassi, Segerlind’07]
  • Circuit complexity [Håstad, Goldmann’91] [Razborov, Wigderson'93] [Beigel, Tarui’94]
  • Data-structures for dynamic problems [Patrascu’10]
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SLIDE 7

Applications of the NOF model

4

  • Branching programs, Ramsey theory [Chandra, Furst, Lipton'83]
  • Quasi-random graphs [Chung, Tetali'93]
  • Proof complexity [Beame, Pitassi, Segerlind’07]
  • Circuit complexity [Håstad, Goldmann’91] [Razborov, Wigderson'93] [Beigel, Tarui’94]
  • Data-structures for dynamic problems [Patrascu’10]

polysize constant-depth circuits with AND, OR, NOT, MODm gates

F is hard to compute for k ≥ log(n) players

F is not in ACC0

[Håstad, Goldmann’91] [Babai, Gál, Kimmel, Lokam’04]

Conjecture: MAJORITY ∉ ACC0 Conjecture: NP ⊈ ACC0

(log n)ω(1)

communication cost:

Best lower bounds so far: ˜

Ω ( n 2k)

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SLIDE 8

Applications of the NOF model

4

  • Branching programs, Ramsey theory [Chandra, Furst, Lipton'83]
  • Quasi-random graphs [Chung, Tetali'93]
  • Proof complexity [Beame, Pitassi, Segerlind’07]
  • Circuit complexity [Håstad, Goldmann’91] [Razborov, Wigderson'93] [Beigel, Tarui’94]
  • Data-structures for dynamic problems [Patrascu’10]

polysize constant-depth circuits with AND, OR, NOT, MODm gates

F is hard to compute for k ≥ log(n) players

F is not in ACC0

[Håstad, Goldmann’91] [Babai, Gál, Kimmel, Lokam’04]

Conjecture: MAJORITY ∉ ACC0 Conjecture: NP ⊈ ACC0

Log(n) barrier problem Find a function that is hard to compute for log(n) or more players in the Number-On-Forehead model.

(log n)ω(1)

communication cost:

Best lower bounds so far: ˜

Ω ( n 2k)

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SLIDE 9

Applications of the NOF model

4

  • Branching programs, Ramsey theory [Chandra, Furst, Lipton'83]
  • Quasi-random graphs [Chung, Tetali'93]
  • Proof complexity [Beame, Pitassi, Segerlind’07]
  • Circuit complexity [Håstad, Goldmann’91] [Razborov, Wigderson'93] [Beigel, Tarui’94]
  • Data-structures for dynamic problems [Patrascu’10]

polysize constant-depth circuits with AND, OR, NOT, MODm gates

F is hard to compute for k ≥ log(n) players

F is not in ACC0

[Håstad, Goldmann’91] [Babai, Gál, Kimmel, Lokam’04]

Conjecture: MAJORITY ∉ ACC0 Conjecture: NP ⊈ ACC0

Log(n) barrier problem Find a function that is hard to compute for log(n) or more players in the Number-On-Forehead model.

(log n)ω(1)

simultaneous

communication cost:

even in the simultaneous NOF model

Best lower bounds so far: ˜

Ω ( n 2k)

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SLIDE 10

Simultaneous Number-On-Forehead model

5

F(x1, x2, x3, x4) = ?

x2, x3, x4 x1, x3, x4 x1, x2, x3 x1, x2, x4

Player 1 Player 2 Player 4 Player 3

One-way communication to a referee, no interactions

Referee

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SLIDE 11

g1 g2 g3 gn

Candidates to break the log(n) barrier: the composed functions

6

x1

1 1

x2

1 1

xk

1 1

n bits k players

  • Input: x1, …, xk ∈ {0,1}n
  • Player i doesn’t see row i

Composed function: f ∘ (g1, …, gn) where f : {0, 1}n → {0, 1}

and gj : {0, 1}k → {0, 1} f

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SLIDE 12

g1 g2 g3 gn

Candidates to break the log(n) barrier: the composed functions

6

x1

1 1

x2

1 1

xk

1 1

n bits k players

  • Input: x1, …, xk ∈ {0,1}n
  • Player i doesn’t see row i

Composed function: f ∘ (g1, …, gn) where f : {0, 1}n → {0, 1}

and gj : {0, 1}k → {0, 1} f

Examples:

  • Generalized Inner Product: MOD2 ○ (AND,…,AND)
  • Disjointness: OR ○ (AND,…,AND)
  • Majority of Majority: MAJ ○ (MAJ,…,MAJ)
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SLIDE 13

g1 g2 g3 gn

Candidates to break the log(n) barrier: the composed functions

6

x1

1 1

x2

1 1

xk

1 1

n bits k players

  • Input: x1, …, xk ∈ {0,1}n
  • Player i doesn’t see row i

Composed function: f ∘ (g1, …, gn) where f : {0, 1}n → {0, 1}

and gj : {0, 1}k → {0, 1} f

[Grolmusz’94] [Babai, Gál, Kimmel, Lokam’04] [Ada, Chattopadhyay, Fawzi, Nguyen’15] Examples:

  • Generalized Inner Product: MOD2 ○ (AND,…,AND)
  • Disjointness: OR ○ (AND,…,AND)
  • Majority of Majority: MAJ ○ (MAJ,…,MAJ)

There is an efficient simultaneous protocol for f ○ (g1,…,gn) when f is symmetric and k ≥ Ω(log n).

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SLIDE 14

Block-composed functions

7

x1

1 1

x2

1 1

… …

xk

1 1

tn bits t bits

g1 gn f

k players

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SLIDE 15

Block-composed functions

7

x1

1 1

x2

1 1

… …

xk

1 1

tn bits t bits

g1 gn f The simultaneous communication cost of MAJ ◦ (MAJ,…,MAJ) is (log n)ω(1) for t ≥ √n and k ≥ Ω(log n).

Unknown even for t = 2

Conjecture [Babai et. al.’04]

k players

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SLIDE 16

Our result

8

1 1 1 1 … … 1 1

t bits

g1 f

If t is constant, there is an efficient simultaneous protocol for f ○ (g1,…,gn) when f, g1, …, gn are symmetric and k ≥ Ω(log n).

MAJ ◦ (MAJ,…,MAJ) cannot break the log n barrier for constant t

Theorem:

gn

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SLIDE 17

Our result

8

1 1 1 1 … … 1 1

t bits

g1 f

If t is constant, there is an efficient simultaneous protocol for f ○ (g1,…,gn) when f, g1, …, gn are symmetric and k ≥ Ω(log n).

MAJ ◦ (MAJ,…,MAJ) cannot break the log n barrier for constant t

Theorem:

gn

Block-width t Model Conditions

[Ada, Chattopadhyay, Fawzi, Nguyen’15]

1 simultaneous f symmetric

[Chattopadhyay, Saks’14]

log log n non-simultaneous f symmetric

[Chattopadhyay, Saks’14]

log n non-simultaneous f, g1, …, gn symmetric

Our result

constant simultaneous f, g1, …, gn symmetric

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SLIDE 18

Our result

9

1 1 1 1 … … 1 1

t bits

g1 f

If t is constant, there is an efficient simultaneous protocol for f ○ (g1,…,gn) when f, g1, …, gn are symmetric and k ≥ Ω(log n).

Roadmap (when k = Θ(log n)):

  • 1. Reduce to the case of equal inner functions g = g1 = … = gn
  • 2. Simultaneous protocol for f◦(g,…,g) with a generalization of [Babai et. al.’04]

MAJ ◦ (MAJ,…,MAJ) cannot break the log n barrier for constant t

Theorem:

gn

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SLIDE 19

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn

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SLIDE 20
  • 1. Each is decomposed in a basis of symmetric functions:

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

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SLIDE 21
  • 1. Each is decomposed in a basis of symmetric functions:
  • 2. For each basis element ma, define the matrix Ma where each Bj is repeated times.

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

ca(gj)

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SLIDE 22
  • 1. Each is decomposed in a basis of symmetric functions:
  • 2. For each basis element ma, define the matrix Ma where each Bj is repeated times.
  • 3. For each ma, compute SUM○(ma,…,ma) on Ma.

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

ca(gj)

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SLIDE 23
  • 1. Each is decomposed in a basis of symmetric functions:
  • 2. For each basis element ma, define the matrix Ma where each Bj is repeated times.
  • 3. For each ma, compute SUM○(ma,…,ma) on Ma.

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

ca(gj)

∑a SUM ∘ (ma, …, ma)(Ma) = ∑a ∑j ca(gj) ⋅ ma(Bj) = ∑j gj(Bj)

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SLIDE 24
  • 1. Each is decomposed in a basis of symmetric functions:
  • 2. For each basis element ma, define the matrix Ma where each Bj is repeated times.
  • 3. For each ma, compute SUM○(ma,…,ma) on Ma.

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

ca(gj)

∑a SUM ∘ (ma, …, ma)(Ma) = ∑a ∑j ca(gj) ⋅ ma(Bj) = ∑j gj(Bj)

Enough to compute since f is symmetric. f ∘ (g1, …, gn)

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SLIDE 25
  • 1. Each is decomposed in a basis of symmetric functions:
  • 2. For each basis element ma, define the matrix Ma where each Bj is repeated times.
  • 3. For each ma, compute SUM○(ma,…,ma) on Ma.

Step 1: equal inner functions

10

x1

1

x2

1 1 1

… …

xk

1 1

f

g1 gn B1 Bn gj

gj(x) = ∑a ca(gj) ⋅ ma(x)

ca(gj)

∑a SUM ∘ (ma, …, ma)(Ma) = ∑a ∑j ca(gj) ⋅ ma(Bj) = ∑j gj(Bj)

Enough to compute since f is symmetric. f ∘ (g1, …, gn)

mod p

Size ≤ k×n2

for prime p ∈ (n,2n)

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SLIDE 26
  • For a k×n matrix M, define y(M) = (y0,…,yk) where yi = #columns with exactly i 1's.

→ Knowing y(M) is enough to compute f○(g,…,g) when f and g are symmetric.

11

Step 3: equation solving protocol

[Babai, Gál, Kimmel, Lokam’04] Protocol for t = 1: x1

1 1 1 1 1 1

x2

1 1 1 1

x3

1 1 1

x4

1 1 1

x5

1 1 1 1 1

y0 = 0 y1 = 1 y2 = 1 y3 = 3 y4 = 1 y5 = 1

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SLIDE 27
  • For a k×n matrix M, define y(M) = (y0,…,yk) where yi = #columns with exactly i 1's.

→ Knowing y(M) is enough to compute f○(g,…,g) when f and g are symmetric.

11

Step 3: equation solving protocol

[Babai, Gál, Kimmel, Lokam’04] Protocol for t = 1: x1

1 1 1 1 1 1

x2

1 1 1 1

x3

1 1 1

x4

1 1 1

x5

1 1 1 1 1

  • For each 1 ≤ i ≤ k, Player i sends y(Mi) where Mi is the submatrix seen by Player i.

→ This will be the only communication part of our protocol. y0 = 0 y1 = 1 y2 = 1 y3 = 3 y4 = 1 y5 = 1

M1

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SLIDE 28

→ The referee computes y(M) and then f○(g,…,g).

  • For a k×n matrix M, define y(M) = (y0,…,yk) where yi = #columns with exactly i 1's.

→ Knowing y(M) is enough to compute f○(g,…,g) when f and g are symmetric.

11

Step 3: equation solving protocol

[Babai, Gál, Kimmel, Lokam’04] Protocol for t = 1: x1

1 1 1 1 1 1

x2

1 1 1 1

x3

1 1 1

x4

1 1 1

x5

1 1 1 1 1

  • For each 1 ≤ i ≤ k, Player i sends y(Mi) where Mi is the submatrix seen by Player i.

→ This will be the only communication part of our protocol.

  • Using y(M1), …, y(Mk), one can define an equation whose only integral solution is y(M).

y0 = 0 y1 = 1 y2 = 1 y3 = 3 y4 = 1 y5 = 1

M1

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SLIDE 29

→ The referee computes y(M) and then f○(g,…,g).

  • For a k×n matrix M, define y(M) = (y0,…,yk) where yi = #columns with exactly i 1's.

→ Knowing y(M) is enough to compute f○(g,…,g) when f and g are symmetric.

11

Step 3: equation solving protocol

[Babai, Gál, Kimmel, Lokam’04] Protocol for t = 1: x1

1 1 1 1 1 1

x2

1 1 1 1

x3

1 1 1

x4

1 1 1

x5

1 1 1 1 1

  • For each 1 ≤ i ≤ k, Player i sends y(Mi) where Mi is the submatrix seen by Player i.

→ This will be the only communication part of our protocol.

  • Using y(M1), …, y(Mk), one can define an equation whose only integral solution is y(M).

y0 = 0 y1 = 1 y2 = 1 y3 = 3 y4 = 1 y5 = 1

M1

We generalize this protocol to t > 1, and show that the corresponding equation admits exactly one integral solution when .

k ≥ Ω(log n)

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SLIDE 30

Conclusion

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  • Efficient simultaneous protocol for non-constant t and/or non-symmetric g1,…,gn
  • Strong lower bound for k ≥ log n players

→ only general method known: discrepancy method and its variants → [Podolskii, Sherstov’17]: first ω(1) lower bound when k ≥ log n for explicit function Our result: MAJ ◦ (MAJ,…,MAJ) cannot break the log n barrier for any constant t

(in fact, any symmetric f○(g1,…,gn))

Future directions: arXiv: 1710.01969

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SLIDE 31

Step 0: decreasing the number of players to k = Θ(log n)

13

If g : Y1,…,Yk → Y is symmetric then is symmetric. g′ (y1, …, yk′ ) = g(y1, …, yk′ , yk′

+1, …, yk)

Lemma:

any fixed values variables

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SLIDE 32

Step 0: decreasing the number of players to k = Θ(log n)

13

If g : Y1,…,Yk → Y is symmetric then is symmetric. g′ (y1, …, yk′ ) = g(y1, …, yk′ , yk′

+1, …, yk)

Lemma:

x1

1

x2

1 1 1

… …

xk’

1 1

⋮ xk

1

f

any fixed values variables

g1 gn

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SLIDE 33

Step 0: decreasing the number of players to k = Θ(log n)

13

If g : Y1,…,Yk → Y is symmetric then is symmetric. g′ (y1, …, yk′ ) = g(y1, …, yk′ , yk′

+1, …, yk)

Lemma:

x1

1

x2

1 1 1

… …

xk’

1 1

⋮ xk

1

f

any fixed values variables

g1 gn x1

1

x2

1 1 1

… …

xk’

1 1

⋮ xk

1

f

g′

1

g′

n