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UID:pretalx-europython-2026-WKBHZW@programme.europython.eu
DTSTART;TZID=CET:20260715T152500
DTEND;TZID=CET:20260715T155500
DESCRIPTION:Python has become the most widely used language in scientific c
 omputing and data science due to its approachable syntax\, vast ecosystem 
 of libraries\, and rapid prototyping capabilities. However\, its interpret
 ed nature often poses a performance bottleneck for computationally intensi
 ve tasks common in High Performance Computing (HPC) used in scientific and
  data work\, such as large-scale simulations\, complex data analysis\, and
  machine learning model training. \n\nEnhancing Python's performance\, the
 refore\, is critical for scientific computing: it allows researchers and e
 ngineers to maintain the productivity and flexibility of the Python enviro
 nment while achieving the necessary speed and scalability to tackle demand
 ing\, real-world HPC problems without needing to switch to lower-level lan
 guages entirely.\n\nIn this talk\, we will review the current state of Pyt
 hon in HPC\, examine the role of key libraries like NumPy and Dask\, and s
 ee how to use PyO3 to create robust Rust bindings for Python in a way that
  simplifies the process of building and distributing packages. We’ll exp
 lore how Rust brings specific advantages to HPC\, including guaranteed mem
 ory safety without garbage collection\, zero-cost abstractions\, and true 
 parallelism.\n\nAttendees will leave with a clear understanding of the 'wh
 y' and 'how' of leveraging Rust in their Python-based HPC workflows\, posi
 tioning them to develop faster\, safer\, and more scalable computational c
 ode.
DTSTAMP:20260524T130702Z
LOCATION:Auditorium Hall (S1)
SUMMARY:Rust for High Performance Computing (HPC) in Python - Cheuk Ting Ho
URL:https://programme.europython.eu/europython-2026/talk/WKBHZW/
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