11,284 research outputs found
Finite Boolean Algebras for Solid Geometry using Julia's Sparse Arrays
The goal of this paper is to introduce a new method in computer-aided
geometry of solid modeling. We put forth a novel algebraic technique to
evaluate any variadic expression between polyhedral d-solids (d = 2, 3) with
regularized operators of union, intersection, and difference, i.e., any CSG
tree. The result is obtained in three steps: first, by computing an independent
set of generators for the d-space partition induced by the input; then, by
reducing the solid expression to an equivalent logical formula between Boolean
terms made by zeros and ones; and, finally, by evaluating this expression using
bitwise operators. This method is implemented in Julia using sparse arrays. The
computational evaluation of every possible solid expression, usually denoted as
CSG (Constructive Solid Geometry), is reduced to an equivalent logical
expression of a finite set algebra over the cells of a space partition, and
solved by native bitwise operators.Comment: revised version submitted to Computer-Aided Geometric Desig
Interference alignment for the MIMO interference channel
We study vector space interference alignment for the MIMO interference
channel with no time or frequency diversity, and no symbol extensions. We prove
both necessary and sufficient conditions for alignment. In particular, we
characterize the feasibility of alignment for the symmetric three-user channel
where all users transmit along d dimensions, all transmitters have M antennas
and all receivers have N antennas, as well as feasibility of alignment for the
fully symmetric (M=N) channel with an arbitrary number of users.
An implication of our results is that the total degrees of freedom available
in a K-user interference channel, using only spatial diversity from the
multiple antennas, is at most 2. This is in sharp contrast to the K/2 degrees
of freedom shown to be possible by Cadambe and Jafar with arbitrarily large
time or frequency diversity.
Moving beyond the question of feasibility, we additionally discuss
computation of the number of solutions using Schubert calculus in cases where
there are a finite number of solutions.Comment: 16 pages, 7 figures, final submitted versio
Julia: A Fresh Approach to Numerical Computing
Bridging cultures that have often been distant, Julia combines expertise from
the diverse fields of computer science and computational science to create a
new approach to numerical computing. Julia is designed to be easy and fast.
Julia questions notions generally held as "laws of nature" by practitioners of
numerical computing:
1. High-level dynamic programs have to be slow.
2. One must prototype in one language and then rewrite in another language
for speed or deployment, and
3. There are parts of a system for the programmer, and other parts best left
untouched as they are built by the experts.
We introduce the Julia programming language and its design --- a dance
between specialization and abstraction. Specialization allows for custom
treatment. Multiple dispatch, a technique from computer science, picks the
right algorithm for the right circumstance. Abstraction, what good computation
is really about, recognizes what remains the same after differences are
stripped away. Abstractions in mathematics are captured as code through another
technique from computer science, generic programming.
Julia shows that one can have machine performance without sacrificing human
convenience.Comment: 37 page
Lie Symmetry Analysis for Cosserat Rods
We consider a subsystem of the Special Cosserat Theory of Rods and construct
an explicit form of its solution that depends on three arbitrary functions in
(s,t) and three arbitrary functions in t. Assuming analyticity of the arbitrary
functions in a domain under consideration, we prove that the obtained solution
is analytic and general. The Special Cosserat Theory of Rods describes the
dynamic equilibrium of 1-dimensional continua, i.e. slender structures like
fibers, by means of a system of partial differential equations.Comment: 12 Pages, 1 Figur
MLI: An API for Distributed Machine Learning
MLI is an Application Programming Interface designed to address the
challenges of building Machine Learn- ing algorithms in a distributed setting
based on data-centric computing. Its primary goal is to simplify the
development of high-performance, scalable, distributed algorithms. Our initial
results show that, relative to existing systems, this interface can be used to
build distributed implementations of a wide variety of common Machine Learning
algorithms with minimal complexity and highly competitive performance and
scalability
Non-linear index coding outperforming the linear optimum
The following source coding problem was introduced by Birk and Kol: a sender
holds a word , and wishes to broadcast a codeword to
receivers, . The receiver is interested in , and has
prior \emph{side information} comprising some subset of the bits. This
corresponds to a directed graph on vertices, where is an edge iff
knows the bit . An \emph{index code} for is an encoding scheme
which enables each to always reconstruct , given his side
information. The minimal word length of an index code was studied by
Bar-Yossef, Birk, Jayram and Kol (FOCS 2006). They introduced a graph
parameter, \minrk_2(G), which completely characterizes the length of an
optimal \emph{linear} index code for . The authors of BBJK showed that in
various cases linear codes attain the optimal word length, and conjectured that
linear index coding is in fact \emph{always} optimal.
In this work, we disprove the main conjecture of BBJK in the following strong
sense: for any and sufficiently large , there is an
-vertex graph so that every linear index code for requires codewords
of length at least , and yet a non-linear index code for
has a word length of . This is achieved by an explicit
construction, which extends Alon's variant of the celebrated Ramsey
construction of Frankl and Wilson.
In addition, we study optimal index codes in various, less restricted,
natural models, and prove several related properties of the graph parameter
\minrk(G).Comment: 16 pages; Preliminary version appeared in FOCS 200
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