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‎Project.toml‎

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XMLDict = "228000da-037f-5747-90a9-8195ccbf91a5"
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[compat]
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AbstractTrees = "0.4"
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CpuId = "0.3"
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JSON = "0.21"
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Scratch = "1"

‎README.md‎

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# PlatformAware.jl
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[![TagBot](https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions/workflows/TagBot.yml/badge.svg)](https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions/workflows/TagBot.yml)
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[![CompatHelper](https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions/workflows/CompatHelper.yml/badge.svg)](https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions/workflows/CompatHelper.yml)
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[![TagBot](https://github.com/PlatformAwareProgramming/PlatformAware.jl/actions/workflows/TagBot.yml/badge.svg)](https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions/workflows/TagBot.yml)
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[![CompatHelper](https://github.com/PlatformAwareProgramming/PlatformAware.jl/actions/workflows/CompatHelper.yml/badge.svg)](https://github.com/PlatformAwareProgramming/PlatformAware.jl/actions/workflows/CompatHelper.yml)
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_A package for improving the practice of **platform-aware programming** in Julia_.
@@ -230,9 +230,9 @@ Therefore, we suggest the following general guideline for package developers who
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3. Identify the target execution platforms to which you want to provide specialized methods for each kernel function. You can choose a set of execution platforms for all kernels, or you can select one or more platforms for each kernel independently. For helping your choice, look at the following information sources:
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- the [table of supported _platform **parameters**_](https://docs.google.com/spreadsheets/d/1n-c4b7RxUduaKV43XrTnt54w-SR1AXgVNI7dN2OkEUc/edit?usp=sharing), which will help you to know which assumptions _PlatformAware.jl_ already allow you to make about the target execution platorm;
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- the database of supported _platform **features**_, where the features of the models of processors and accelerators that are currently suported by _PlatformAware.jl_ are described:
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- AMD [accelerators](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/src/features/qualifiers/amd/db-accelerators.AMD.csv) and [processors](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/src/features/qualifiers/amd/db-processors.AMD.csv);
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- Intel [accelerators](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/src/features/qualifiers/intel/db-accelerators.Intel.csv) and [processors](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/src/features/qualifiers/intel/db-processors.Intel.csv);
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- NVIDIA [accelerators](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/src/features/qualifiers/nvidia/db-accelerators.NVIDIA.csv).
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- AMD [accelerators](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/src/features/qualifiers/amd/db-accelerators.AMD.csv) and [processors](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/src/features/qualifiers/amd/db-processors.AMD.csv);
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- Intel [accelerators](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/src/features/qualifiers/intel/db-accelerators.Intel.csv) and [processors](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/src/features/qualifiers/intel/db-processors.Intel.csv);
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- NVIDIA [accelerators](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/src/features/qualifiers/nvidia/db-accelerators.NVIDIA.csv).
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4. For each platform you select, define a set of assumptions about its features that will guide your implementation decisions. In fact, it is possible to define different assumptions for the same platform, leading to multiple implementations of a kernel for the same platform. For example, you might decide to implement different parallel algorithms to solve a problem according to the number of nodes and the interconnection characteristics of a cluster.
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Contributions are very welcome, as are feature requests and suggestions.
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Please [open an issue](https://github.com/decarvalhojunior-fh/PlatformAware.jl) if you encounter any problems.
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Please [open an issue](https://github.com/PlatformAwareProgramming/PlatformAware.jl) if you encounter any problems.
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# License
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_PlatformAware.jl_ is licensed under the [MIT License](https://github.com/decarvalhojunior-fh/PlatformAware.jl/blob/master/LICENSE)
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_PlatformAware.jl_ is licensed under the [MIT License](https://github.com/PlatformAwareProgramming/PlatformAware.jl/blob/master/LICENSE)
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[build-img]: https://img.shields.io/github/workflow/status/JuliaEarth/ImageQuilting.jl/CI
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[build-url]: https://github.com/decarvalhojunior-fh/PlatformAware.jl/actions
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[build-url]: https://github.com/PlatformAwareProgramming/PlatformAware.jl/actions

‎src/PlatformAware.jl‎

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export
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@platform,
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@quantifier,
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@atleast,
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@atmost,
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@between,
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@just,
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@unlimited,
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@api,
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PlatformFeature,
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PlatformType,
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QuantifierFeature,
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QualifierFeature,
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Query,
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Yes,
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No,
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Maintainer,
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Provider,
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OnPremise,
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CloudProvider,
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MachineFamily,

‎src/features/default/Platform.toml‎

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[node]
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node_count = 1
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node_provider = "OnPremise"
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node_virtual = "No"
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node_dedicated = "Yes"

‎src/features/detection.jl‎

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database_path = @get_scratch!("database_path")
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procdb_intel_url = "https://raw.githubusercontent.com/platform-aware-programming/PlatformAware.jl/master/src/features/qualifiers/intel/db-processors.Intel.csv"
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procdb_amd_url = "https://raw.githubusercontent.com/platform-aware-programming/PlatformAware.jl/master/src/features/qualifiers/amd/db-processors.AMD.csv"
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accdb_intel_url = "https://raw.githubusercontent.com/platform-aware-programming/PlatformAware.jl/master/src/features/qualifiers/intel/db-accelerators.Intel.csv"
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accdb_amd_url = "https://raw.githubusercontent.com/platform-aware-programming/PlatformAware.jl/master/src/features/qualifiers/amd/db-accelerators.AMD.csv"
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accdb_nvidia_url = "https://raw.githubusercontent.com/platform-aware-programming/PlatformAware.jl/master/src/features/qualifiers/nvidia/db-accelerators.NVIDIA.csv"
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procdb_intel_url = "https://raw.githubusercontent.com/PlatformAwareProgramming/PlatformAware.jl/master/src/features/qualifiers/intel/db-processors.Intel.csv"
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procdb_amd_url = "https://raw.githubusercontent.com/PlatformAwareProgramming/PlatformAware.jl/master/src/features/qualifiers/amd/db-processors.AMD.csv"
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accdb_intel_url = "https://raw.githubusercontent.com/PlatformAwareProgramming/PlatformAware.jl/master/src/features/qualifiers/intel/db-accelerators.Intel.csv"
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accdb_amd_url = "https://raw.githubusercontent.com/PlatformAwareProgramming/PlatformAware.jl/master/src/features/qualifiers/amd/db-accelerators.AMD.csv"
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accdb_nvidia_url = "https://raw.githubusercontent.com/PlatformAwareProgramming/PlatformAware.jl/master/src/features/qualifiers/nvidia/db-accelerators.NVIDIA.csv"
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# procdb_intel_fname = "/home/heron/Dropbox/Copy/ufc_mdcc_hpc/PlatformAware/PlatformAware.jl/src/features/qualifiers/intel/db-processors.Intel.csv" #joinpath(database_path,basename(procdb_intel_url))
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# procdb_amd_fname = "/home/heron/Dropbox/Copy/ufc_mdcc_hpc/PlatformAware/PlatformAware.jl/src/features/qualifiers/amd/db-processors.AMD.csv" #joinpath(database_path,basename(procdb_amd_url))
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get!(cdict,c[:id],c[:value])
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end
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processor_core_count = parse(Int64,cdict["enabledcores"])
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processor_core_threadscount = parse(Int64,cdict["threads"])
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processor_core_threads_count = parse(Int64,cdict["threads"])
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push!(l,(p["product"],processor_core_count, processor_core_threadscount,lc))
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push!(l,(p["product"],processor_core_count, processor_core_threads_count,lc))
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end
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‎src/features/features.jl‎

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# Licensed under the MIT License. See LICENCE in the project root.
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# ------------------------------------------------------------------
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abstract type PlatformFeature end
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abstract type PlatformType end
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abstract type QuantifierFeature <: PlatformFeature end
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abstract type QualifierFeature <: PlatformFeature end
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abstract type QuantifierFeature <: PlatformType end
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abstract type QualifierFeature <: PlatformType end
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@enum FeatureType qualifier=1 api_qualifier quantifier
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:node_memory_bandwidth => quantifier,
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:node_memory_type => qualifier,
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:node_memory_frequency => quantifier,
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:node_coworker_count => qualifier,
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:processor_count => quantifier,
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:processor_manufacturer => qualifier,
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:processor_microarchitecture => qualifier,
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function get_quantifier_from_number(n)
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if n>0
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magnitude = Dict(0 => "", 1 => "K", 2 => "M", 3 => "G", 4 => "T", 5 => "P", 6 => "E")
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l = log(2,n)
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a = round(l)
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a = floor(l)
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b = isinteger(l) ? a : a + 1;
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# the following loop separates a and b in multiplier*magnitude (see the POPL's paper).
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# let A = 2^a
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m=0
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m1=0
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# loop invariant: A = 2^a * 2^(10*m)
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a = a - 10
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m1 = m1 + 1
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end
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m2=0
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while b>9
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b = b - 10
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m2 = m2 + 1
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a_str = "AtLeast" * string(Integer(2^a)) * magnitude[m]
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b_str = "AtMost" * string(Integer(2^b)) * magnitude[m]
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a_str = "AtLeast" * string(Integer(2^a)) * magnitude[m1]
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b_str = "AtMost" * string(Integer(2^b)) * magnitude[m2]
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a_str = "AtLeast0"
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b_str = "AtMost0"
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a_type = getfield(@__MODULE__, Meta.parse(a_str))
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Tuple{a_type,b_type}
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Tuple{a_type,b_type,n}
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getfield(@__MODULE__, Meta.parse(feature))
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function check_blank_feature(parameter_id, feature, default_platform_types)
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function check_blank_feature(parameter_id, feature, platform_feature_default)
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if (feature == "na")
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default_platform_types[parameter_id]
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platform_feature_default[parameter_id]
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elseif (feature == "unset")
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default_platform_types[parameter_id]
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platform_feature_default[parameter_id]
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default_platform_types[parameter_id]
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platform_feature_default[parameter_id]
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default_platform_types[parameter_id]
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platform_feature_default[parameter_id]
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function get_api_qualifier(api_string, default_platform_types)
212+
function get_api_qualifier(api_string, platform_feature_default)
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function loadFeaturesSection!(dict, actual_platform_arguments, default_platform_types)
233+
function loadFeaturesSection!(dict, platform_feature, platform_feature_default)
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if ("0" in keys(dict))
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dict = dict["0"]
231237
end
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233239
for (parameter_id, feature) in dict
234240
p = Meta.parse(parameter_id)
235-
v0 = check_blank_feature(p, feature, default_platform_types)
241+
v0 = check_blank_feature(p, feature, platform_feature_default)
236242
v = if (isnothing(v0))
237-
feature_type[p] == qualifier ? get_qualifier(feature) : feature_type[p] == api_qualifier ? get_api_qualifier(feature, default_platform_types) : get_quantifier(feature)
243+
feature_type[p] == qualifier ? get_qualifier(feature) : feature_type[p] == api_qualifier ? get_api_qualifier(feature, platform_feature_default) : get_quantifier(feature)
238244
else
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v0
240246
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actual_platform_arguments[p]= v
247+
platform_feature[p]= v
242248
end
243249
end
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function loadFeatures!(dict, default_platform_types, actual_platform_arguments)
251+
function loadFeatures!(dict, platform_feature_default, platform_feature)
246252
loadDBs!()
247253
for key in ["node", "processor", "accelerator", "memory", "storage", "interconnection"]
248-
loadFeaturesSection!(dict[key], actual_platform_arguments, default_platform_types)
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loadFeaturesSection!(dict[key], platform_feature, platform_feature_default)
249255
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250256
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‎src/features/qualifiers/amd/db-processors.AMD.csv‎

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,,processor_core_count,processor_clock,processor_core_threadscount,processor_isa,processor_simd,processor_microarchitecture,processor,processor_manufacturer,processor_tdp,processor_core_L1_size,processor_core_L2_size,processor_L3_size,node_memory_bandwidth,node_memory_type
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,,processor_core_count,processor_clock,processor_core_threads_count,processor_isa,processor_simd,processor_microarchitecture,processor,processor_manufacturer,processor_tdp,processor_core_L1_size,processor_core_L2_size,processor_L3_size,node_memory_bandwidth,node_memory_type
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AMD;Turion,TL64,2,2.2G,2,64-bit,MMX;Now3Dx;SSE;SSE2;SSE3,unset,AMDTurion_TL64,AMD,35,unset,1MB,unset,667M,DDR2
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AMD;Turion,TL60,2,2.0G,2,64-bit,MMX;Now3Dx;SSE;SSE2;SSE3,unset,AMDTurion_TL60,AMD,31,unset,1MB,unset,667M,DDR2
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AMD;Turion,TL56,2,1.8G,2,64-bit,MMX;Now3Dx;SSE;SSE2;SSE3,unset,AMDTurion_TL56,AMD,31,unset,unset,unset,unset,unset

‎src/features/qualifiers/common.jl‎

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abstract type ISA_IA_64 <: ProcessorISA end
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export ISA_x86_32, ISA_x86, ISA_x86_64, ISA_AMD_64, ISA_x86_64_v1, ISA_x86_64_v2, ISA_x86_64_v3, ISA_x86_64_v4, ISA_IA_64
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119+
abstract type WorkerCount end
120+
abstract type NoCoworkers <: WorkerCount end
121+
abstract type PerNode <: WorkerCount end
122+
abstract type PerProcessor <: WorkerCount end
123+
abstract type PerCore <: WorkerCount end
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abstract type PerThread <: WorkerCount end
125+
abstract type PerVCPU <: WorkerCount end
126+
abstract type Unmapped <: WorkerCount end
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128+
export PerNode, PerProcessor, PerCore, PerThread, PerVCPU

‎src/features/qualifiers/intel/db-processors.Intel.csv‎

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,,processor_core_count,processor_clock,processor_core_threadscount,processor_isa,processor_simd,processor_microarchitecture,processor,processor_manufacturer,processor_tdp,processor_core_L1_size,processor_core_L2_size,processor_L3_size
1+
,,processor_core_count,processor_clock,processor_core_threads_count,processor_isa,processor_simd,processor_microarchitecture,processor,processor_manufacturer,processor_tdp,processor_core_L1_size,processor_core_L2_size,processor_L3_size
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Intel;Xeon;W,3275M,28,2.50G,56,64-bit,AVX-512,CascadeLake,IntelXeon_W_3275M,Intel,205,unset,unset,unset
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Intel;Xeon;W,3265M,24,2.70G,48,64-bit,AVX-512,CascadeLake,IntelXeon_W_3265M,Intel,205,unset,unset,unset
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Intel;Xeon;W,3245M,16,3.20G,32,64-bit,AVX-512,CascadeLake,IntelXeon_W_3245M,Intel,205,unset,unset,unset

‎src/features/quantifiers/atleast.jl‎

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# automated declaration of at-least quantifier types
66

7-
abstract type AtLeast0 <: QuantifierFeature end
7+
abstract type AtLeast0 <: QuantifierFeature end; export AtLeast0
88

99
let mul_super = 0
1010
mag_ = ""

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