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{
"title":"PyAETNA: Python Accelerated Exoplanet Toolkit and Noise Analysis",
"upload_type":"software",
"description":"A JAX-based framework for the joint Bayesian modelling of exoplanet light curves and radial velocities, configured from a single YAML file and run on a GPU or on CPUs. This archive contains release 4.0.0 and the paper_benchmarks package that reproduces the results of the software paper.",
"license":"MIT",
"creators":[
{"name":"Scandariato, G.","affiliation":"INAF - Osservatorio Astrofisico di Catania"},
{"name":"Singh, V.","affiliation":"INAF - Osservatorio Astrofisico di Catania"},
{"name":"Arena, C.","affiliation":"INAF - Osservatorio Astrofisico di Catania"},
{"name":"Scavo, S.","affiliation":"INAF - Osservatorio Astrofisico di Catania"}
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@@ -56,7 +56,7 @@ reproduced by PyAETNA. Last column: likelihood evaluations of the laptop CPU run
- Against **pyaneti**, with the same ensemble MCMC, PyAETNA is 1.2 to 1.8 times faster.
- A **GPU** makes PyAETNA up to 8.5 times faster than the CPU of the same machine, and it is never
slower (the smallest ratio, 1.02, is for K2-100 (NS, laptop)). Against the reference codes on their
CPUs, the GPU runs are 1.1 to 137 times faster, except for K2-140 against PyORBIT, TOI-5398 against PyORBIT.
CPUs, the GPU runs are 1.1 to 137 times faster; the exceptions, where the reference code on its CPUs is as fast or faster, are K2-140 against PyORBIT, TOI-5398 against PyORBIT.
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@@ -290,7 +290,7 @@ reproduced by PyAETNA. Last column: likelihood evaluations of the laptop CPU run
- Against **pyaneti**, with the same ensemble MCMC, PyAETNA is {v.get('faster_pyaneti','–')} times faster.
- A **GPU** makes PyAETNA up to {v['gpu_own_max']} times faster than the CPU of the same machine, and it is never
slower (the smallest ratio, {v['gpu_own_min']}, is for {v['gpu_own_min_name']}). Against the reference codes on their
CPUs, the GPU runs are {v['gpu_vs_ref']} times faster, except for{v['gpu_vs_ref_slower_names']}.
CPUs, the GPU runs are {v['gpu_vs_ref']} times faster; the exceptions, where the reference code on its CPUs is as fast or faster, are{v['gpu_vs_ref_slower_names']}.
