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| seminars [2025-03-18] – Martin Ziegler | seminars [2026-01-01] (current) – [Extensions of the skein algorithm for link polynomials I] Martin Ziegler | ||
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| ====== Seminar on Theoretical Computer Science, Logic, and Real Computation ====== | ====== Seminar on Theoretical Computer Science, Logic, and Real Computation ====== | ||
| + | * [[Seminars# | ||
| * [[Seminars# | * [[Seminars# | ||
| * [[Seminars# | * [[Seminars# | ||
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| * [[Seminars# | * [[Seminars# | ||
| * [[Seminars# | * [[Seminars# | ||
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| + | ===== 2026 ===== | ||
| + | |||
| + | ====Extensions of the skein algorithm for link polynomials I==== | ||
| + | * January 15, 14h KST | ||
| + | * N1 #422 and online | ||
| + | * Alexander Stoimenov | ||
| + | |||
| + | This talk gives some explanation about the Millett-Ewing skein algorithm for link polynomials | ||
| + | and subsequent modifications and extensions. Plan is: | ||
| + | - Details of the Millett-Ewing skein algorithm | ||
| + | - The Stack | ||
| + | - Alexander-variable truncations | ||
| + | - Parallelizing | ||
| + | - Applications to quasipositivity | ||
| + | - Braid-skein algorithm and non-Alexander variable truncations | ||
| ===== 2025 ===== | ===== 2025 ===== | ||
| + | |||
| + | ====Computing with the Millett-Ewing notation==== | ||
| + | * December 12, 11am KST | ||
| + | * N1 #422 | ||
| + | * Alexander Stoimenov (Dongguk U) | ||
| + | |||
| + | This talk gives some introduction about the notation of link diagrams developed by Millett-Ewing in the late 80s for calculating link polynomials. | ||
| + | I explain how this notation is used by Knotscape (for this see [[https:// | ||
| + | before giving some details on the Millett-Ewing algorithm and (my) several subsequent modifications and extensions. | ||
| + | |||
| + | ====XpLUTo: Modelling Bulk Parallel Processing in RAM via Lookup Tables==== | ||
| + | * August 12, 4pm KST | ||
| + | * E3-1 #4420 and online | ||
| + | * Nguyên Trần Bảo (HCMUT and KAIST) | ||
| + | |||
| + | Processing-in-memory (PIM) has been investigated for its ability to | ||
| + | perform bulk data operations while eliminating data movement, which is a major | ||
| + | performance bottleneck. However, existing designs, regardless of how minimal, | ||
| + | still require modifications to the physical memory circuitry. Moreover, each | ||
| + | proposed operation introduces different primitives, inherently hindering the development | ||
| + | of a general design capable of supporting all operations. In this work, | ||
| + | we propose XPLUTO, a new parallel architecture model that leverages the capabilities | ||
| + | of PIM. Our key observation is that, in the worst case, any complex | ||
| + | operation can be implemented via a lookup table (precomputation and query), | ||
| + | which can be viewed as a SIMD (single-instruction multiple-data) operation. | ||
| + | Based on this insight, we focus on designing algorithms built upon SIMD operations, | ||
| + | with asymptotic costs estimated according to lookup table performance. | ||
| + | So far, XPLUTO has demonstrated the ability to emulate various problems, | ||
| + | including sorting, addition, and prefix operations. | ||
| + | |||
| ====Integer factorization of matrices and 4-dimensional genera of knots==== | ====Integer factorization of matrices and 4-dimensional genera of knots==== | ||
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| library written in C++ and in a derived current approach in | library written in C++ and in a derived current approach in | ||
| Python. | Python. | ||
| + | |||
| ===== 2024 ===== | ===== 2024 ===== | ||