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Artjoms Sinkarovs
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2020 – today
- 2024
- [e2]Aaron Hsu, Artjoms Sinkarovs:
Proceedings of the 10th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, ARRAY 2024, Copenhagen, Denmark, 25 June 2024. ACM 2024 [contents] - [i4]Artjoms Sinkarovs, Thomas Koopman, Sven-Bodo Scholz:
Correctness is Demanding, Performance is Frustrating. CoRR abs/2406.10405 (2024) - 2023
- [c17]Thorsten Altenkirch, Ambrus Kaposi, Artjoms Sinkarovs, Tamás Végh:
Combinatory Logic and Lambda Calculus Are Equal, Algebraically. FSCD 2023: 24:1-24:19 - [c16]Artjoms Sinkarovs, Thomas Koopman, Sven-Bodo Scholz:
Rank-Polymorphism for Shape-Guided Blocking. FHPNC 2023: 1-14 - [e1]Troels Henriksen, Artjoms Sinkarovs:
Proceedings of the 9th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, ARRAY 2023, Orlando, FL, USA, 18 June 2023. ACM 2023 [contents] - 2022
- [c15]Artjoms Sinkarovs, Sven-Bodo Scholz:
Parallel scan as a multidimensional array problem. ARRAY@PLDI 2022: 1-11 - [c14]Thorsten Altenkirch, Ambrus Kaposi, Artjoms Sinkarovs, Tamás Végh:
The Münchhausen Method in Type Theory. TYPES 2022: 10:1-10:20 - 2021
- [c13]Artjoms Sinkarovs
, Jesper Cockx
:
Extracting the power of dependent types. GPCE 2021: 83-95 - [c12]Artjoms Sinkarovs
, Hans-Nikolai Vießmann
, Sven-Bodo Scholz
:
Array languages make neural networks fast. ARRAY@PLDI 2021: 39-50 - [i3]Artjoms Sinkarovs, Jesper Cockx:
Choosing is Losing: How to combine the benefits of shallow and deep embeddings through reflection. CoRR abs/2105.10819 (2021) - 2020
- [c11]Artjoms Sinkarovs
:
Multi-dimensional Arrays with Levels. MSFP@ETAPS 2020: 57-71
2010 – 2019
- 2019
- [c10]Max Baird, Sven-Bodo Scholz, Artjoms Sinkarovs
, Leonardo Bautista-Gomez:
Checkpointing Kernel Executions of MPI+CUDA Applications. Euro-Par Workshops 2019: 694-706 - [c9]Sven-Bodo Scholz, Artjoms Sinkarovs:
Tensor comprehensions in SaC. IFL 2019: 15:1-15:13 - [c8]Artjoms Sinkarovs
, Robert Bernecky, Sven-Bodo Scholz:
Convolutional neural networks in APL. ARRAY@PLDI 2019: 69-79 - [i2]Artjoms Sinkarovs, Hans-Nikolai Vießmann
, Sven-Bodo Scholz:
Array Languages Make Neural Networks Fast. CoRR abs/1912.05234 (2019) - 2018
- [c7]Max Baird, Christian Fensch, Sven-Bodo Scholz, Artjoms Sinkarovs
:
A Lightweight Approach to GPU Resilience. Euro-Par Workshops 2018: 826-838 - [c6]Hans-Nikolai Vießmann
, Artjoms Sinkarovs
, Sven-Bodo Scholz:
Extended Memory Reuse: An Optimisation for Reducing Memory Allocations. IFL 2018: 107-118 - [c5]Artjoms Sinkarovs
, Robert Bernecky, Hans-Nikolai Vießmann
, Sven-Bodo Scholz:
A Rosetta Stone for array languages. ARRAY@PLDI 2018: 1-10 - 2017
- [c4]Artjoms Sinkarovs
, Sven-Bodo Scholz, Robert J. Stewart
, Hans-Nikolai Vießmann
:
Recursive Array Comprehensions in a Call-by-Value Language. IFL 2017: 5:1-5:12 - [i1]Artjoms Sinkarovs, Sven-Bodo Scholz:
A Lambda Calculus for Transfinite Arrays: Unifying Arrays and Streams. CoRR abs/1710.03832 (2017) - 2016
- [j2]Artjoms Sinkarovs
, Sven-Bodo Scholz
:
Type-driven data layouts for improved vectorisation. Concurr. Comput. Pract. Exp. 28(7): 2092-2119 (2016) - 2015
- [c3]Hans-Nikolai Vießmann
, Sven-Bodo Scholz
, Artjoms Sinkarovs
, Brian Bainbridge, Brian Hamilton, Simon Flower:
Making fortran legacy code more functional: using the BGS* geomagnetic field modelling system as an example. IFL 2015: 11:1-11:13 - 2014
- [j1]Artjoms Sinkarovs
, Sven-Bodo Scholz
, Robert Bernecky, Roeland Douma, Clemens Grelck:
SaC/C formulations of the all-pairs N-body problem and their performance on SMPs and GPGPUs. Concurr. Comput. Pract. Exp. 26(4): 952-971 (2014) - 2013
- [c2]Artjoms Sinkarovs, Sven-Bodo Scholz
:
Semantics-preserving data layout transformations for improved vectorisation. FHPC@ICFP 2013: 59-70 - [c1]Artjoms Sinkarovs
, Sven-Bodo Scholz
:
Data layout inference for code vectorisation. HPCS 2013: 527-534
Coauthor Index
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