6,339 research outputs found
A Novel SAT-Based Approach to the Task Graph Cost-Optimal Scheduling Problem
The Task Graph Cost-Optimal Scheduling Problem consists in scheduling a certain number of interdependent tasks onto a set of heterogeneous processors (characterized by idle and running rates per time unit), minimizing the cost of the entire process. This paper provides a novel formulation for this scheduling puzzle, in which an optimal solution is computed through a sequence of Binate Covering Problems, hinged within a Bounded Model Checking paradigm. In this approach, each covering instance, providing a min-cost trace for a given schedule depth, can be solved with several strategies, resorting to Minimum-Cost Satisfiability solvers or Pseudo-Boolean Optimization tools. Unfortunately, all direct resolution methods show very low efficiency and scalability. As a consequence, we introduce a specialized method to solve the same sequence of problems, based on a traditional all-solution SAT solver. This approach follows the "circuit cofactoring" strategy, as it exploits a powerful technique to capture a large set of solutions for any new SAT counter-example. The overall method is completed with a branch-and-bound heuristic which evaluates lower and upper bounds of the schedule length, to reduce the state space that has to be visited. Our results show that the proposed strategy significantly improves the blind binate covering schema, and it outperforms general purpose state-of-the-art tool
The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing
The risk of reinsurance portfolios covering globally occurring natural
catastrophes, such as earthquakes and hurricanes, is quantified by employing
simulations. These simulations are computationally intensive and require large
amounts of data to be processed. The use of many-core hardware accelerators,
such as the Intel Xeon Phi and the NVIDIA Graphics Processing Unit (GPU), are
desirable for achieving high-performance risk analytics. In this paper, we set
out to investigate how accelerators can be employed in risk analytics, focusing
on developing parallel algorithms for Aggregate Risk Analysis, a simulation
which computes the Probable Maximum Loss of a portfolio taking both primary and
secondary uncertainties into account. The key result is that both hardware
accelerators are useful in different contexts; without taking data transfer
times into account the Phi had lowest execution times when used independently
and the GPU along with a host in a hybrid platform yielded best performance.Comment: A modified version of this article is accepted to the Computers and
Electrical Engineering Journal under the title - "The Hardware Accelerator
Debate: A Financial Risk Case Study Using Many-Core Computing"; Blesson
Varghese, "The Hardware Accelerator Debate: A Financial Risk Case Study Using
Many-Core Computing," Computers and Electrical Engineering, 201
Error Correcting Codes for Distributed Control
The problem of stabilizing an unstable plant over a noisy communication link
is an increasingly important one that arises in applications of networked
control systems. Although the work of Schulman and Sahai over the past two
decades, and their development of the notions of "tree codes"\phantom{} and
"anytime capacity", provides the theoretical framework for studying such
problems, there has been scant practical progress in this area because explicit
constructions of tree codes with efficient encoding and decoding did not exist.
To stabilize an unstable plant driven by bounded noise over a noisy channel one
needs real-time encoding and real-time decoding and a reliability which
increases exponentially with decoding delay, which is what tree codes
guarantee. We prove that linear tree codes occur with high probability and, for
erasure channels, give an explicit construction with an expected decoding
complexity that is constant per time instant. We give novel sufficient
conditions on the rate and reliability required of the tree codes to stabilize
vector plants and argue that they are asymptotically tight. This work takes an
important step towards controlling plants over noisy channels, and we
demonstrate the efficacy of the method through several examples.Comment: 39 page
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