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Stochastic Optimization of Floating Point Programs with Tunable Precision
64-bit x86 x86-64, Binary Markov Chain Monte Carlo MCMC Stochastic Search SMT Floating-Point Precision
2016/5/24
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in highperformance computing. However, the competing constraints of transformation correct...
Advances in convex optimization: Interior-point methods, cone programming, and applications
Convex optimization linear programming nonlinear convex programming program robust
2015/8/11
In this talk I will give an overview of some major developments in convex optimization that have emerged over the last ten years or so. The basic idea is that convex problems are fundamentally tractab...
Temperature control of high-performance multi-core platforms using convex optimization
Thermal-aware design temperature control dynamic frequency scaling static and dynamic optimization
2015/8/10
With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradi...
PID design by convex-concave optimization
PID controller optimize the design can robustness constraints convex-concave programming data
2015/8/7
This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method ad...
Matrix-free convex optimization modeling
Convex optimization modeling framework convex optimization into the program linear function matrix graphic coding
2015/8/7
We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way tha...
Disciplined convex stochastic programming: A new framework for stochastic optimization
Convex stochastic programming modeling mathematics DCSP modeling
2015/8/7
We introduce disciplined convex stochastic programming (DCSP), a modeling framework that can significantly lower the barrier for modelers to specify and solve convex stochastic optimization problems, ...