1,480 research outputs found
LIPIcs
We study space complexity and time-space trade-offs with a focus not on peak memory usage but on overall memory consumption throughout the computation. Such a cumulative space measure was introduced for the computational model of parallel black pebbling by [Alwen and Serbinenko ’15] as a tool for obtaining results in cryptography. We consider instead the non- deterministic black-white pebble game and prove optimal cumulative space lower bounds and trade-offs, where in order to minimize pebbling time the space has to remain large during a significant fraction of the pebbling. We also initiate the study of cumulative space in proof complexity, an area where other space complexity measures have been extensively studied during the last 10–15 years. Using and extending the connection between proof complexity and pebble games in [Ben-Sasson and Nordström ’08, ’11] we obtain several strong cumulative space results for (even parallel versions of) the resolution proof system, and outline some possible future directions of study of this, in our opinion, natural and interesting space measure
On the Relative Strength of Pebbling and Resolution
The last decade has seen a revival of interest in pebble games in the context
of proof complexity. Pebbling has proven a useful tool for studying
resolution-based proof systems when comparing the strength of different
subsystems, showing bounds on proof space, and establishing size-space
trade-offs. The typical approach has been to encode the pebble game played on a
graph as a CNF formula and then argue that proofs of this formula must inherit
(various aspects of) the pebbling properties of the underlying graph.
Unfortunately, the reductions used here are not tight. To simulate resolution
proofs by pebblings, the full strength of nondeterministic black-white pebbling
is needed, whereas resolution is only known to be able to simulate
deterministic black pebbling. To obtain strong results, one therefore needs to
find specific graph families which either have essentially the same properties
for black and black-white pebbling (not at all true in general) or which admit
simulations of black-white pebblings in resolution. This paper contributes to
both these approaches. First, we design a restricted form of black-white
pebbling that can be simulated in resolution and show that there are graph
families for which such restricted pebblings can be asymptotically better than
black pebblings. This proves that, perhaps somewhat unexpectedly, resolution
can strictly beat black-only pebbling, and in particular that the space lower
bounds on pebbling formulas in [Ben-Sasson and Nordstrom 2008] are tight.
Second, we present a versatile parametrized graph family with essentially the
same properties for black and black-white pebbling, which gives sharp
simultaneous trade-offs for black and black-white pebbling for various
parameter settings. Both of our contributions have been instrumental in
obtaining the time-space trade-off results for resolution-based proof systems
in [Ben-Sasson and Nordstrom 2009].Comment: Full-length version of paper to appear in Proceedings of the 25th
Annual IEEE Conference on Computational Complexity (CCC '10), June 201
Reversibility and Adiabatic Computation: Trading Time and Space for Energy
Future miniaturization and mobilization of computing devices requires energy
parsimonious `adiabatic' computation. This is contingent on logical
reversibility of computation. An example is the idea of quantum computations
which are reversible except for the irreversible observation steps. We propose
to study quantitatively the exchange of computational resources like time and
space for irreversibility in computations. Reversible simulations of
irreversible computations are memory intensive. Such (polynomial time)
simulations are analysed here in terms of `reversible' pebble games. We show
that Bennett's pebbling strategy uses least additional space for the greatest
number of simulated steps. We derive a trade-off for storage space versus
irreversible erasure. Next we consider reversible computation itself. An
alternative proof is provided for the precise expression of the ultimate
irreversibility cost of an otherwise reversible computation without
restrictions on time and space use. A time-irreversibility trade-off hierarchy
in the exponential time region is exhibited. Finally, extreme
time-irreversibility trade-offs for reversible computations in the thoroughly
unrealistic range of computable versus noncomputable time-bounds are given.Comment: 30 pages, Latex. Lemma 2.3 should be replaced by the slightly better
``There is a winning strategy with pebbles and erasures for
pebble games with , for all '' with appropriate
further changes (as pointed out by Wim van Dam). This and further work on
reversible simulations as in Section 2 appears in quant-ph/970300
Reversible Simulation of Irreversible Computation by Pebble Games
Reversible simulation of irreversible algorithms is analyzed in the stylized
form of a `reversible' pebble game. While such simulations incur little
overhead in additional computation time, they use a large amount of additional
memory space during the computation. The reacheable reversible simulation
instantaneous descriptions (pebble configurations) are characterized
completely. As a corollary we obtain the reversible simulation by Bennett and
that among all simulations that can be modelled by the pebble game, Bennett's
simulation is optimal in that it uses the least auxiliary space for the
greatest number of simulated steps. One can reduce the auxiliary storage
overhead incurred by the reversible simulation at the cost of allowing limited
erasing leading to an irreversibility-space tradeoff. We show that in this
resource-bounded setting the limited erasing needs to be performed at precise
instants during the simulation. We show that the reversible simulation can be
modified so that it is applicable also when the simulated computation time is
unknown.Comment: 11 pages, Latex, Submitted to Physica
Understanding Space in Proof Complexity: Separations and Trade-offs via Substitutions
For current state-of-the-art DPLL SAT-solvers the two main bottlenecks are
the amounts of time and memory used. In proof complexity, these resources
correspond to the length and space of resolution proofs. There has been a long
line of research investigating these proof complexity measures, but while
strong results have been established for length, our understanding of space and
how it relates to length has remained quite poor. In particular, the question
whether resolution proofs can be optimized for length and space simultaneously,
or whether there are trade-offs between these two measures, has remained
essentially open.
In this paper, we remedy this situation by proving a host of length-space
trade-off results for resolution. Our collection of trade-offs cover almost the
whole range of values for the space complexity of formulas, and most of the
trade-offs are superpolynomial or even exponential and essentially tight. Using
similar techniques, we show that these trade-offs in fact extend to the
exponentially stronger k-DNF resolution proof systems, which operate with
formulas in disjunctive normal form with terms of bounded arity k. We also
answer the open question whether the k-DNF resolution systems form a strict
hierarchy with respect to space in the affirmative.
Our key technical contribution is the following, somewhat surprising,
theorem: Any CNF formula F can be transformed by simple variable substitution
into a new formula F' such that if F has the right properties, F' can be proven
in essentially the same length as F, whereas on the other hand the minimal
number of lines one needs to keep in memory simultaneously in any proof of F'
is lower-bounded by the minimal number of variables needed simultaneously in
any proof of F. Applying this theorem to so-called pebbling formulas defined in
terms of pebble games on directed acyclic graphs, we obtain our results.Comment: This paper is a merged and updated version of the two ECCC technical
reports TR09-034 and TR09-047, and it hence subsumes these two report
Inapproximability of the Standard Pebble Game and Hard to Pebble Graphs
Pebble games are single-player games on DAGs involving placing and moving
pebbles on nodes of the graph according to a certain set of rules. The goal is
to pebble a set of target nodes using a minimum number of pebbles. In this
paper, we present a possibly simpler proof of the result in [CLNV15] and
strengthen the result to show that it is PSPACE-hard to determine the minimum
number of pebbles to an additive term for all , which improves upon the currently known additive constant hardness of
approximation [CLNV15] in the standard pebble game. We also introduce a family
of explicit, constant indegree graphs with nodes where there exists a graph
in the family such that using constant pebbles requires moves
to pebble in both the standard and black-white pebble games. This independently
answers an open question summarized in [Nor15] of whether a family of DAGs
exists that meets the upper bound of moves using constant pebbles
with a different construction than that presented in [AdRNV17].Comment: Preliminary version in WADS 201
Approximating Cumulative Pebbling Cost Is Unique Games Hard
The cumulative pebbling complexity of a directed acyclic graph is defined
as , where the minimum is taken over all
legal (parallel) black pebblings of and denotes the number of
pebbles on the graph during round . Intuitively, captures
the amortized Space-Time complexity of pebbling copies of in parallel.
The cumulative pebbling complexity of a graph is of particular interest in
the field of cryptography as is tightly related to the
amortized Area-Time complexity of the Data-Independent Memory-Hard Function
(iMHF) [AS15] defined using a constant indegree directed acyclic
graph (DAG) and a random oracle . A secure iMHF should have
amortized Space-Time complexity as high as possible, e.g., to deter brute-force
password attacker who wants to find such that . Thus, to
analyze the (in)security of a candidate iMHF , it is crucial to
estimate the value but currently, upper and lower bounds for
leading iMHF candidates differ by several orders of magnitude. Blocki and Zhou
recently showed that it is -Hard to compute , but
their techniques do not even rule out an efficient
-approximation algorithm for any constant . We
show that for any constant , it is Unique Games hard to approximate
to within a factor of .
(See the paper for the full abstract.)Comment: 28 pages, updated figures and corrected typo
RiffleScrambler - a memory-hard password storing function
We introduce RiffleScrambler: a new family of directed acyclic graphs and a
corresponding data-independent memory hard function with password independent
memory access. We prove its memory hardness in the random oracle model.
RiffleScrambler is similar to Catena -- updates of hashes are determined by a
graph (bit-reversal or double-butterfly graph in Catena). The advantage of the
RiffleScrambler over Catena is that the underlying graphs are not predefined
but are generated per salt, as in Balloon Hashing. Such an approach leads to
higher immunity against practical parallel attacks. RiffleScrambler offers
better efficiency than Balloon Hashing since the in-degree of the underlying
graph is equal to 3 (and is much smaller than in Ballon Hashing). At the same
time, because the underlying graph is an instance of a Superconcentrator, our
construction achieves the same time-memory trade-offs.Comment: Accepted to ESORICS 201
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