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Everything about Automatic vectorization

Case in parallel computing

Automatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once. For example, modern conventional computers, including specialized supercomputers, typically have vector operations that simultaneously perform operations such as the following four additions : Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Automatic vectorizationA 5-minute orientation
  2. Skim a recent paper: Selective Element and Two Orders Vectorization Networks for Automatic Depression Severity Diagnosis via Facial ChangesInfluential work since 2022
  3. Pick up a classic book: Optimal pitch thrust-vector angle and benefits for all flight regimesThe most-reprinted book on the subject
  4. Read the landmark paper: A vector space model for automatic indexingCited 5,056 times
  5. Go sideways: AltiVecA closely related topic
  6. Go sideways: Single instruction, multiple dataA closely related topic

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🗂️ The subject at a glance

  1. Background
  2. Guarantees
  3. Theory
  4. General framework
  5. Run-time vs. compile-time
  6. Techniques
  7. Manual vectorization

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics