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A Compact, MachineIndependent Peephole Optimizer
"... Object code optimizers pay dividends but are usually ad hoc and machinedependent. They would be easier to understand if, instead of performing many ad hoc optimization, they performed a few general optimizations that give the same effect. They would be easier to implement if they were machineindep ..."
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and parametrized by symbolic machine descriptions. This paper describes such a compact, machineindependent peephole optimizer.
Eel: Machineindependent executable editing
 In Proceedings of the SIGPLAN ’95 Conference on Programming Language Design and Implementation (PLDI
, 1995
"... EEL (Executable Editing Library) is a library for building tools to analyze and modify an executable (compiled) program. The systems and languages communities have built many tools for error detection, fault isolation, architecture translation, performance measurement, simulation, and optimization u ..."
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Cited by 297 (12 self)
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using this approach of modifying executables. Currently, however, tools of this sort are difficult and timeconsuming to write and are usually closely tied to a particular machine and operating system. EEL supports a machine and systemindependent editing model that enables tool builders to modify
Exact Matrix Completion via Convex Optimization
, 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
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Cited by 842 (26 self)
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by solving a simple convex optimization program. This program finds the matrix with minimum nuclear norm that fits the data. The condition above assumes that the rank is not too large. However, if one replaces the 1.2 exponent with 1.25, then the result holds for all values of the rank. Similar results hold
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 973 (32 self)
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query point q 2 R d , and ffl ? 0, a (1 + ffl)approximate nearest neighbor of q can be computed in O(c d;ffl log n) time, where c d;ffl d d1 + 6d=ffle d is a factor depending only on dimension and ffl. In general, we show that given an integer k 1, (1 + ffl)approximations to the k nearest neighbors
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
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Cited by 1487 (20 self)
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Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear
On the algorithmic implementation of multiclass kernelbased vector machines
 Journal of Machine Learning Research
"... In this paper we describe the algorithmic implementation of multiclass kernelbased vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic ob ..."
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Cited by 546 (13 self)
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In this paper we describe the algorithmic implementation of multiclass kernelbased vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic
MachineIndependent Compiler Optimizations for the U of T DSP Architecture
"... There are two kinds of compiler optimizations: machinedependent optimizations and machineindependent optimizations. For specialized architectures such as a DSP architecture, machinedependent optimizations play a very important role, because these optimizations seek to exploit the special hardware ..."
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There are two kinds of compiler optimizations: machinedependent optimizations and machineindependent optimizations. For specialized architectures such as a DSP architecture, machinedependent optimizations play a very important role, because these optimizations seek to exploit the special
Fast Parallel Algorithms for ShortRange Molecular Dynamics
 JOURNAL OF COMPUTATIONAL PHYSICS
, 1995
"... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of interatomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
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Cited by 631 (7 self)
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. The algorithms are tested on a standard LennardJones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers  the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray YMP and C90 algorithm shows
The University of Florida sparse matrix collection
 NA DIGEST
, 1997
"... The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural enginee ..."
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Cited by 529 (17 self)
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The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural
Composable memory transactions
 In Symposium on Principles and Practice of Parallel Programming (PPoPP
, 2005
"... Atomic blocks allow programmers to delimit sections of code as ‘atomic’, leaving the language’s implementation to enforce atomicity. Existing work has shown how to implement atomic blocks over wordbased transactional memory that provides scalable multiprocessor performance without requiring changes ..."
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Cited by 502 (42 self)
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leaving the block. This paper takes a fourpronged approach to improving performance: (1) we introduce a new ‘direct access ’ implementation that avoids searching threadprivate logs, (2) we develop compiler optimizations to reduce the amount of logging (e.g. when a thread accesses the same data
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