Building designers are increasingly relying on complex fenestration systems to reduce energy consumed for lighting and HVAC in low energy buildings. Radiance, a lighting simulation program, has been used to conduct daylighting simulations for complex fenestration systems. Depending on the configurations, the simulation can take hours or even days using a personal computer. This paper describes how to accelerate the matrix multiplication portion of a Radiance three-phase daylight simulation by conducting parallel computing on heterogeneous hardware of a personal computer. The algorithm was optimized and the computational part was implemented in parallel using OpenCL. The speed of new approach was evaluated using various daylighting simulation cases on a multicore central processing unit and a graphics processing unit. Based on the measurements and analysis of the time usage for the Radiance daylighting simulation, further speedups can be achieved by using fast I/O devices and storing the data in a binary format.

10adaylighting simulation10agraphics processing unit10amulticore central processing unit10aOpenCL10aparallel computing1 aZuo, Wangda1 aMcNeil, Andrew1 aWetter, Michael1 aLee, Eleanor, S. uhttps://windows.lbl.gov/publications/acceleration-matrix-multiplication-radiance-three-phase-daylighting-simulations01205nas a2200133 4500008003900000245006900039210006900108260001200177520072300189100003100912700002000943700001600963856009200979 2012 d00aValidation of the Window Model of the Modelica Buildings Library0 aValidation of the Window Model of the Modelica Buildings Library c07/20123 aThis paper describes the validation of the window model of the free open-source Modelica Buildings library. This paper starts by describing the physical modeling assumptions of the window model. The window model can be used to calculate the thermal and angular properties of glazing systems. It can also be used for steady-state simulation of heat transfer mechanism in glazing systems. We present simulation results obtained by comparing the window model with WINDOW 6 the well established simulation tool for steady-state heat transfer in glazing systems. We also present results obtained by comparing the window model with measurements carried out in a test cell at the Lawrence Berkeley National Laboratory.

1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aZuo, Wangda uhttps://windows.lbl.gov/publications/validation-window-model-modelica-buildings-library01247nas a2200157 4500008004100000245009300041210006900134260003100203300001500234520064900249100001600898700001900914700002000933700002100953856011500974 2011 eng d00aAcceleration of Radiance for Lighting Simulation by using Parallel Computing with OpenCL0 aAcceleration of Radiance for Lighting Simulation by using Parall aSydney, Australiac11/2011 ap. 110-1173 aThis study attempted to accelerate annual daylighting simulations for fenestration systems in Radiance ray-tracing program. The algorithm was optimized to reduce both the redundant data input/output operations and floating-point operations. To further accelerate the simulation speed, calculation for matrices multiplications was implemented in parallel on a graphics processing unit using OpenCL, a cross-platform parallel programming language. Numerical experiments show that combination of above measures can speed up the annual daylighting simulations 101.7 times or 28.6 times when sky vector has 146 or 2306 elements, respectively.

1 aZuo, Wangda1 aMcNeil, Andrew1 aWetter, Michael1 aLee, Eleanor, S. uhttps://windows.lbl.gov/publications/acceleration-radiance-lighting-simulation-using-parallel-computing-opencl01933nam a2200109 4500008003900000245006800039210006400107260008800171520144300259100002001702856010101722 2011 d00aGenOpt Generic Optimization Program, User Manual, Version 3.1.00 aGenOpt Generic Optimization Program User Manual Version 310 aBerkeleybSimulation Research Group, Lawrence Berkeley National Laboratoryc12/20113 aGenOpt is an optimization program for the minimization of a cost function that is evaluated by an external simulation program. It has been developed for optimization problems where the cost function is computationally expensive and its derivatives are not available or may not even exist. GenOpt can be coupled to any simulation programthat reads its input from text files and writes its output to text files. The independent variables can be continuous variables (possibly with lower and upper bounds), discrete variables, or both, continuous and discrete variables. Constraints on dependent variables can be implemented using penalty or barrier functions. GenOpt uses parallel computing to evaluate the simulations. GenOpt has a library with local and global multi-dimensional and one-dimensional optimization algorithms, and algorithms for doing parametric runs. An algorithm interface allows adding new minimization algorithms without knowing the details of the program structure. GenOpt is written in Java so that it is platform independent. The platform independence and the general interface make GenOpt applicable to a wide range of optimization problems. GenOpt has not been designed for linear programming problems, quadratic programming problems, and problems where the gradient of the cost function is available. For such problems, as well as for other problems, special tailored software exists that is more efficient.

1 aWetter, Michael uhttps://windows.lbl.gov/publications/genopt-generic-optimization-program-user-manual-version-31001975nas a2200121 4500008004100000245009400041210006900135260002600204520146700230100002001697700001801717856011801735 2008 eng d00aA Modular Building Controls Virtual Test Bed for the Integration of Heterogeneous Systems0 aModular Building Controls Virtual Test Bed for the Integration o aBerkeley, CAc08/20083 aThis paper describes the Building Controls Virtual Test Bed (BCVTB) that is currently under development at Lawrence Berkeley National Laboratory. An earlier prototype linked EnergyPlus with controls hardware through embedded SPARK models and demonstrated its value in more cost-effective envelope design and improved controls sequences for the San Francisco Federal Building. The BCVTB presented here is a more modular design based on a middleware that we built using Ptolemy II, a modular software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. Our additions to Ptolemy II allow users to couple to Ptolemy II a prototype version of EnergyPlus, MATLAB/Simulink or other simulation programs for data exchange during run-time. In future work we will also implement a BACnet interface that allows coupling BACnet compliant building automation systems to Ptolemy II. We will present the architecture of the BCVTB and explain how users can add their own simulation programs to the BCVTB. We will then present an example application in which the building envelope and the HVAC system was simulated in EnergyPlus, the supervisory control logic was simulated in MATLAB/Simulink and Ptolemy II was used to exchange data during run-time and to provide real-time visualization as the simulation progresses.

1 aWetter, Michael1 aHaves, Philip uhttps://windows.lbl.gov/publications/modular-building-controls-virtual-test-bed-integration-heterogeneous-systems