mplex the models are. If we are running multi-room E+ studies, that will take far longer to calculate.
Rhino/Grasshopper = <1%
Generating Radiance .ill files = 88%
Processing .ill files into DA, etc. = ~2%
E+ = 10%
Parallelizing Grasshopper:
My first instinct is to avoid this problem by running GH on one computer only. Creating the batch files is very fast. The trick will be sending the radiance and E+ batch files to multiple computers. Perhaps a “round-robin” approach could send each iteration to another node on the network until all iterations are assigned. I have no idea how to do that but hope that it is something that can be executed within grasshopper, perhaps a custom code module. I think GH can set a directory for Radiance and E+ to save all final files to. We can set this to a local server location so all runs output to the same location. It will likely run slower than it would on the C:drive, but those losses are acceptable if we can get parallelization to work.
I’m concerned about post-processing of the Radiance/E+ runs. For starters, Honeybee calculates DA after it runs the .ill files. This doesn’t take very long, but it is a separate process that is not included in the original Radiance batch file. Any other data manipulation we intend to automatically run in GH will be left out of the batch file as well. Consolidating the results into a format that Design Explorer or Pollination can read also takes a bit of post-processing. So, it seems to me that we may want to split up the GH automation as follows:
Initiate
Parametrically generate geometry
Assign input values, material, etc.
Generate radiance/ E+ batch files for all iterations
Calculate
Calc separate runs of Radiance/E+ in parallel via network clusters. Each run will be a unique iteration.
Save all temp files to single server location on server
Post Processing
Run a GH script from a single computer. Translate .ill files or .idf files into custom metrics or graphics (DA, ASE, %shade down, net solar gain, etc.)
Collect final data in single location (excel document) to be read by Design Explorer or Pollination.
The above workflow avoids having to parallelize GH. The consequence is that we can’t parallelize any post-processing routines. This may be easier to implement in the short term, but long term we should try to parallelize everything.
Parallelizing EnergyPlus/Radiance:
I agree that the best way to enable large numbers of iterations is to set up multiple unique runs of radiance and E+ on separate computers. I don’t see the incentive to split individual runs between multiple processors because the modular nature of the iterative parametric models does this for us. Multiple unique runs will simplify the post-processing as well.
It seems that the advantages of optimizing matrix based calculations (3-5 phase methods) are most beneficial when iterations are run in series. Is it possible for multiple iterations running on different CPUs to reference the same matrices stored in a common location? Will that enable parallel computation to also benefit from reusing pre-calculated information?
Clustering computers and GPU based calculations:
Clustering unused computers seems like a natural next step for us. Our IT guru told me that we need come kind of software to make this happen, but that he didn’t know what that would be. Do you know what Penn State uses? You mentioned it is a text-only Linux based system. Can you please elaborate so I can explain to our IT department?
Accelerad is a very exciting development, especially for rpict and annual glare analysis. I’m concerned that the high quality GPU’s required might limit our ability to implement it on a large scale within our office. Does it still work well on standard GPU’s? The computer cluster method can tap into resources we already have, which is a big advantage. Our current workflow uses image-based calcs sparingly, because grid-based simulations gather the critical information much faster. The major exception is glare. Accelerad would enable luminance-based glare metrics, especially annual glare metrics, to be more feasible within fast-paced projects. All of that is a good thing.
So, both clusters and GPU-based calcs are great steps forward. Combining both methods would be amazing, especially if it is further optimized by the computational methods you are working on.
Moving forward, I think I need to explore if/how GH can send iterations across a cluster network of some kind and see what it will take to implement Accelerad. I assume some custom scripting will be necessary.…
rcles in the corner af a rectangle, just as drawn in the screenshot i attached.
i first created a rectangle, split it up into curves so that i get the endpoints, on which i created the circles. but i dont nee the circles located at the corner, they have to be moved a bit into the middle, so that the yellow line, drawn in the screenshot, is just as long as the radius of the circle. thinking about this the whole day, i really appreciate any kind of help!
thanx a lot!!
…
se enseñan los principios de modelado básico y orgánico en Rhinoceros. En Grasshopper se estudian los principios de Parametrización, panelización y análisis en Grasshopper, así como el proceso de manufactura digital para maquinaria de corte Láser y CNC.
UN solo pago anticipado $5,000.00
Pagos diferidos $5,500.00*
*reserva tu lugar con el 50%
De lunes a viernes de 10 am a 18 pm
Del 23 al 27 de julio de 2012
DURACION: 40 HORAS
SESIONES: 5 DE 8 HORAS
o info@dimensiontallerdigital.com
informes al 55 (50 16 0634) con Mayri Gallegos (o al cel. 55 28 85 24 73)
Incluye material para corte digital.…
Horticulture and Landscape in same time.
The most common plastic materials used as agricultural films are the low density polyethylene (LDPE, with a density less than 0.93 kg m−3), the copolymer of ethylene and vinyl-acetate (EVA)
Also here you can find the characteristics of the flexible materials for greenhouse covers (adapted from CPA, 1992 and Tesi, 2001) as much as i get.
UV-PE Film ( UV-PE~ polyethylene Long life or UV)
Thickness (mm) = 0.18
Direct PAR transmissivity (%) = 90
Diffuse PAR transmissivity (%)= 86
Long-wave IR transmissivity (%)= 65
EVA Film ( EVA~Ethylene vinyl-acetate copolymer)
Thickness (mm) = 0.18
Direct PAR transmissivity (%) = 90
Diffuse PAR transmissivity (%)= 76
Long-wave IR transmissivity (%)= 27
and here you will find the global heat transfer coefficient’ (K in W m−2 °C−1) for the above greenhouse covering materials, measured under normalized conditions (temperatures: exterior: −10°C, interior: +20°C, wind: 4 m s−1). (Source: Nisen and Deltour, 1986.)
Cover Clear sky Overcast Sky
Single PE 8.8-9.0 7.1- 7.2
Single EVA 7.8 6.6
Note : the PAR radiation (photosynthetically active or photoactive radiation and its the amounts to 45–50% of the global radiation; Berninger, 1989)
The name PAR is used to designate the radiation with wavelengths useful for plant photosynthesis. It is accepted that the PAR radiation ranges from 400 to 700 nm (McCree, 1972), although some authors consider the PAR from 350 to 850 nm.
The composition of the radiation changes with time, as a function of the Sun’s elevation and the cloudiness. When the Sun is low over the horizon, the short wavelengths are reduced (less UV and more red). The clouds reduce the amount of energy, greatly decreasing the NIR.
The PAR proportion in relation to the global radiation increases with scattering (diffusion). It is lower with clear sky and in the summer (45–48%).
kind regards
rafat …
the blurring boundaries between art, architecture and engineering
Organised by computational designer and architecture teacher Francesco Cingolani in collaboration with parisian design firm Hugh Dutton Associates and La Gâité Lyrique, DESIGN by DATA focuses on the use of parametric design tools such as grasshopper and advanced plug-ins in order to design complex architectural features driven by environmental data and passive energy design strategies.
HUGH DUTTON ASSOCIATES is a unique team of people striving to create a synthesis of poetic intent and physical reality thought their designs. With this focus in mind, Hugh Dutton Associates recently designed the CLIMATE RIBBON™ in Miami, a project that combines precision engineering and environmental design with an elegant sculptural form: an exciting union of art and science.
EARLY BIRDS still available (prices will rise after the 16th of June)
More information and applications :
designbydata.org…
the blurring boundaries between art, architecture and engineering
Organised by computational designer and architecture teacher Francesco Cingolani in collaboration with parisian design firm Hugh Dutton Associates and La Gâité Lyrique, DESIGN by DATA focuses on the use of parametric design tools such as grasshopper and advanced plug-ins in order to design complex architectural features driven by environmental data and passive energy design strategies.
HUGH DUTTON ASSOCIATES is a unique team of people striving to create a synthesis of poetic intent and physical reality thought their designs. With this focus in mind, Hugh Dutton Associates recently designed the CLIMATE RIBBON™ in Miami, a project that combines precision engineering and environmental design with an elegant sculptural form: an exciting union of art and science.
EARLY BIRDS still available (prices will rise after the 15th of October)
More information and applications :
designbydata.org…
er are required. General 3d knowledge is a plus.
More details : http://www.immaginoteca.pro/data-trees-workshop-introduction-to-computational-design-in-architecture/…