Ascend to Science: Exploration of AI Chips for Scientific Computing | Paper Citation Record

Observation 0e296cb7-fd5d-4790-a332-f040ad928640 · outbound

This paper cites High-performance computing at a crossroads.Science, 387(6736):829–831, 2025.

Ascend to Science: Exploration of AI Chips for Scientific Computing High-performance computing at a crossroads.Science, 387(6736):829–831, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.334226Z

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Observation f7c89602-3c3d-474d-8472-e5c1aef0da7d · outbound

This paper cites The co-evolution of computational physics and high-performance computing.

Ascend to Science: Exploration of AI Chips for Scientific Computing The co-evolution of computational physics and high-performance computing

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.393270Z

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Observation 80e685a0-4713-4e4d-bc90-7a738a424850 · outbound

This paper cites The design process for google’s training chips: Tpuv2 and tpuv3.IEEE Micro, 41(2):56–63, 2021.

Ascend to Science: Exploration of AI Chips for Scientific Computing The design process for google’s training chips: Tpuv2 and tpuv3.IEEE Micro, 41(2):56–63, 2021

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.470661Z

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Observation fbe886d7-166d-46aa-97ee-d7a1bcd03233 · outbound

This paper cites an unresolved cited work.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.548816Z

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Observation fc1724e3-ee44-45d5-b4c5-d820614e7666 · outbound

This paper cites Serving large language models on huawei cloudmatrix384, 2025.

Ascend to Science: Exploration of AI Chips for Scientific Computing Serving large language models on huawei cloudmatrix384, 2025

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.661749Z

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Observation 0ebb1712-d342-4b7e-afaa-cfc033c5b415 · outbound

This paper cites Distributed training of large language models on aws trainium.

Ascend to Science: Exploration of AI Chips for Scientific Computing Distributed training of large language models on aws trainium

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.757099Z

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Observation 8534bd62-4898-4ba9-b03f-e47c51c49017 · outbound

This paper cites Harrison, David Carlson, Smeet Chheda, Anthony Curtis, Firat Coskun, Raul Gonzalez, Daniel Wood, and Nikolay A.

Ascend to Science: Exploration of AI Chips for Scientific Computing Harrison, David Carlson, Smeet Chheda, Anthony Curtis, Firat Coskun, Raul Gonzalez, Daniel Wood, and Nikolay A

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.928716Z

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Observation 1a9f3153-727c-4e6e-bc87-df609f00fb2c · outbound

This paper cites Nvidia hopper h100 gpu: Scaling performance.IEEE Micro, 43(3):9–17, 2023.

Ascend to Science: Exploration of AI Chips for Scientific Computing Nvidia hopper h100 gpu: Scaling performance.IEEE Micro, 43(3):9–17, 2023

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.023062Z

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Observation d646bcf0-51db-4efc-bf26-53213205bb1e · outbound

This paper cites Hpl-mxp benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation.Int.

Ascend to Science: Exploration of AI Chips for Scientific Computing Hpl-mxp benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation.Int

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.102878Z

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Observation bb89f51d-fa4a-4ada-b3f9-42d478b1cf9b · outbound

This paper cites Hardware Trends Impacting Floating-Point Computations In Scientific Applications.

Ascend to Science: Exploration of AI Chips for Scientific Computing Hardware Trends Impacting Floating-Point Computations In Scientific Applications

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.176107Z

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Observation 23cc8d9d-3303-4ea1-a89f-1784ebb2df50 · outbound

This paper cites Implementation and numerical techniques for one eflop/s hpl-ai benchmark on fugaku.

Ascend to Science: Exploration of AI Chips for Scientific Computing Implementation and numerical techniques for one eflop/s hpl-ai benchmark on fugaku

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.254004Z

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Observation 5748fc44-eaa4-419c-b1a8-b4c507649959 · outbound

This paper cites Climbing the summit and pushing the frontier of mixed precision benchmarks at extreme scale.

Ascend to Science: Exploration of AI Chips for Scientific Computing Climbing the summit and pushing the frontier of mixed precision benchmarks at extreme scale

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.360202Z

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Observation 3a318ad3-1137-47ee-bcd3-9cbdbb61f64f · outbound

This paper cites Unlocking high performance with low-bit npus and cpus for highly optimized hpl-mxp on cloud brain ii.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unlocking high performance with low-bit npus and cpus for highly optimized hpl-mxp on cloud brain ii

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.561329Z

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Observation 7f2c4517-3499-4487-95f7-fc061c3bb533 · outbound

This paper cites Error-free transformations of matrix multiplication by using fast routines of matrix multiplication and its applications.Numerical Algorithms, 59(1):95– 118, 2012.

Ascend to Science: Exploration of AI Chips for Scientific Computing Error-free transformations of matrix multiplication by using fast routines of matrix multiplication and its applications.Numerical Algorithms, 59(1):95– 118, 2012

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.635532Z

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Observation 058a9eac-bbc4-4a1a-ac83-cab7a15d0b8d · outbound

This paper cites Egemm-tc: accelerating scientific computing on tensor cores with extended precision.

Ascend to Science: Exploration of AI Chips for Scientific Computing Egemm-tc: accelerating scientific computing on tensor cores with extended precision

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.637881Z

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Observation 507b1a3d-bd7e-4b55-bfba-82fd3c53bcd0 · outbound

This paper cites Efficiently emulating high-bitwidth computation with low-bitwidth hardware.

Ascend to Science: Exploration of AI Chips for Scientific Computing Efficiently emulating high-bitwidth computation with low-bitwidth hardware

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.717360Z

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Observation 85303ef1-0db0-466a-8bd5-c1349f5f6ea9 · outbound

This paper cites SGEMM-cube: Precision-Recovery FP32 GEMM Approximation on Ascend NPUs with FP16 Matrix Engines.

Ascend to Science: Exploration of AI Chips for Scientific Computing SGEMM-cube: Precision-Recovery FP32 GEMM Approximation on Ascend NPUs with FP16 Matrix Engines

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.855605Z

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Observation 5748591f-4eb1-4a55-bdcf-4036f7fc5e99 · outbound

This paper cites Xu, Samuel Rodriguez, Sebastien Cayrols, Pawel Tabaszewski, and Victor Podlozhnyuk.

Ascend to Science: Exploration of AI Chips for Scientific Computing Xu, Samuel Rodriguez, Sebastien Cayrols, Pawel Tabaszewski, and Victor Podlozhnyuk

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:27.974542Z

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Observation dfbb6538-3593-48d7-9519-5708c42060bd · outbound

This paper cites Malone, Joonho Lee, Adam G.

Ascend to Science: Exploration of AI Chips for Scientific Computing Malone, Joonho Lee, Adam G

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:28.322832Z

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Observation f56c6a0d-7c6a-406f-a21f-45bac5e859cf · outbound

This paper cites an unresolved cited work.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:28.480214Z

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Observation 38f4b598-2424-49f4-87b2-68ec6d79138f · outbound

This paper cites High performance implementations of the 2d ising model on gpus.Computer Physics Communications, 256:107473, 2020.

Ascend to Science: Exploration of AI Chips for Scientific Computing High performance implementations of the 2d ising model on gpus.Computer Physics Communications, 256:107473, 2020

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:28.650481Z

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Observation 5e085d13-ac59-436c-aec6-f65dbc960299 · outbound

This paper cites Bezgin, Aaron B.

Ascend to Science: Exploration of AI Chips for Scientific Computing Bezgin, Aaron B

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:28.803210Z

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Observation 26fde474-a53d-4e41-a56c-bb8168149674 · outbound

This paper cites Buhendwa, and Nikolaus A.

Ascend to Science: Exploration of AI Chips for Scientific Computing Buhendwa, and Nikolaus A

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:28.998359Z

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Observation bcc815db-4245-4daf-aa92-3bec7a97e850 · outbound

This paper cites Hardy, et al.

Ascend to Science: Exploration of AI Chips for Scientific Computing Hardy, et al

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.159450Z

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Observation 2c338cb3-aa6a-48a5-9bae-d7a4217ed880 · outbound

This paper cites FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs.

Ascend to Science: Exploration of AI Chips for Scientific Computing FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.307677Z

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Observation d919a4e2-8140-4fd7-a53c-ebb11921d06f · outbound

This paper cites Elsevier, 2020.

Ascend to Science: Exploration of AI Chips for Scientific Computing Elsevier, 2020

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.506341Z

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Observation de36d72c-da20-4c84-8f18-716da4b6f818 · outbound

This paper cites Harnessing gpu tensor cores for fast fp16 arithmetic to speed up mixed-precision iterative refinement solvers.

Ascend to Science: Exploration of AI Chips for Scientific Computing Harnessing gpu tensor cores for fast fp16 arithmetic to speed up mixed-precision iterative refinement solvers

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.602732Z

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Observation 344b798b-8db4-45a1-9615-4cae01f4cd6c · outbound

This paper cites The linpack benchmark: past, present and future.Concur- rency and Computation: practice and experience, 15(9):803–820, 2003.

Ascend to Science: Exploration of AI Chips for Scientific Computing The linpack benchmark: past, present and future.Concur- rency and Computation: practice and experience, 15(9):803–820, 2003

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.736752Z

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Observation 90ebb2ad-31bd-42f0-b0f9-286137651e13 · outbound

This paper cites Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions.SIAM review, 53(2):217–288, 2011.

Ascend to Science: Exploration of AI Chips for Scientific Computing Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions.SIAM review, 53(2):217–288, 2011

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:29.881962Z

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Observation 02af18e7-4069-4afb-b6ac-042a1082c639 · outbound

This paper cites Randomized block krylov methods for stronger and faster approximate singular value decomposition.Advances in neural information processing systems, 28, 2015.

Ascend to Science: Exploration of AI Chips for Scientific Computing Randomized block krylov methods for stronger and faster approximate singular value decomposition.Advances in neural information processing systems, 28, 2015

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.041063Z

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Observation 383108b4-6e0d-456a-b38f-f1dd9a3197ae · outbound

This paper cites Streaming low-rank matrix approximation with an application to scientific simulation.SIAM Journal on Scientific Computing, 41(4):A2430–A2463, 2019.

Ascend to Science: Exploration of AI Chips for Scientific Computing Streaming low-rank matrix approximation with an application to scientific simulation.SIAM Journal on Scientific Computing, 41(4):A2430–A2463, 2019

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.230489Z

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Observation 317351e2-1a6d-45a4-b04a-c0f3fa0f996a · outbound

This paper cites Fast algorithms for singular value decomposition and the inverse of nearly low-rank matrices.National Science Review, 10(6):nwad083, 2023.

Ascend to Science: Exploration of AI Chips for Scientific Computing Fast algorithms for singular value decomposition and the inverse of nearly low-rank matrices.National Science Review, 10(6):nwad083, 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.380305Z

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Observation a7815457-1faf-4104-b97e-a7633749a500 · outbound

This paper cites Quantum computing: A taxonomy, systematic review and future directions.Software: Practice and Experience, 52(1):92–136, 2022.

Ascend to Science: Exploration of AI Chips for Scientific Computing Quantum computing: A taxonomy, systematic review and future directions.Software: Practice and Experience, 52(1):92–136, 2022

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.565344Z

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Observation 93d94bca-cf35-4933-be14-a482ee8bdcfd · outbound

This paper cites Nielsen and I.

Ascend to Science: Exploration of AI Chips for Scientific Computing Nielsen and I

Reference 35

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Observation aee02832-50b2-49d0-ac76-8ece57c6dc92 · outbound

This paper cites an unresolved cited work.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unresolved cited work

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.819367Z

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Observation d3a2d7cb-fecd-4683-9463-6e372115a331 · outbound

This paper cites an unresolved cited work.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unresolved cited work

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:30.946544Z

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Observation 8d761637-5e94-4987-9762-f43d3743a14f · outbound

This paper cites Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando G.

Ascend to Science: Exploration of AI Chips for Scientific Computing Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando G

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.124076Z

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Observation dc78ba8d-46a0-4f8f-88cd-784be3d112c0 · outbound

This paper cites Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable monte carlo simulation.npj Computational Materials, 11(1):267, 2025.

Ascend to Science: Exploration of AI Chips for Scientific Computing Revealing nanostructures in high-entropy alloys via machine-learning accelerated scalable monte carlo simulation.npj Computational Materials, 11(1):267, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.219357Z

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Observation 671d4100-a740-4c13-9852-05d877acda37 · outbound

This paper cites Smc-x: A distributed, scalable monte carlo simulation method for chemically complex alloys.Journal of Chemical Theory and Computation, 21(24):12784–12795, 12 2025.

Ascend to Science: Exploration of AI Chips for Scientific Computing Smc-x: A distributed, scalable monte carlo simulation method for chemically complex alloys.Journal of Chemical Theory and Computation, 21(24):12784–12795, 12 2025

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.365524Z

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Observation b7c69376-8b9d-4910-b84d-ee935c56b876 · outbound

This paper cites Schneider.

Ascend to Science: Exploration of AI Chips for Scientific Computing Schneider

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.437615Z

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Observation b883a099-f110-4604-b44a-86811f70e9de · outbound

This paper cites High performance monte carlo simulation of ising model on tpu clusters.

Ascend to Science: Exploration of AI Chips for Scientific Computing High performance monte carlo simulation of ising model on tpu clusters

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.548683Z

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Observation 865c886d-64a7-461a-9fb7-f9f09454b2c8 · outbound

This paper cites Gpu-accelerated gibbs ensemble monte carlo simulations of lennard-jonesium.Computer Physics Communications, 184(12):2662– 2669, 2013.

Ascend to Science: Exploration of AI Chips for Scientific Computing Gpu-accelerated gibbs ensemble monte carlo simulations of lennard-jonesium.Computer Physics Communications, 184(12):2662– 2669, 2013

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.631790Z

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Observation 861f2e9a-5ffb-4e79-a33c-8a5330bca14f · outbound

This paper cites Scalable parallel monte carlo algorithm for atomistic simulations of precipitation in alloys.Physical Review B, 85(18):184203, May 2012.

Ascend to Science: Exploration of AI Chips for Scientific Computing Scalable parallel monte carlo algorithm for atomistic simulations of precipitation in alloys.Physical Review B, 85(18):184203, May 2012

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.733311Z

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Observation a1070a9c-db7d-48de-acf8-c223fceabe09 · outbound

This paper cites Thompson, H.

Ascend to Science: Exploration of AI Chips for Scientific Computing Thompson, H

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:31.976780Z

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Observation 337610a0-93b8-4005-83cb-060c1358f7b9 · outbound

This paper cites Machine learning for high-entropy alloys: Progress, challenges and opportunities.Progress in Materials Science, 131:101018, 2023.

Ascend to Science: Exploration of AI Chips for Scientific Computing Machine learning for high-entropy alloys: Progress, challenges and opportunities.Progress in Materials Science, 131:101018, 2023

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.154870Z

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Observation 2edc0f08-d2f0-4abd-bb1c-714ca04da9c5 · outbound

This paper cites Designing complex concentrated alloys with quantum machine learning and language modeling.Matter, 7(10):3433–3446, 2026/02/01 2024.

Ascend to Science: Exploration of AI Chips for Scientific Computing Designing complex concentrated alloys with quantum machine learning and language modeling.Matter, 7(10):3433–3446, 2026/02/01 2024

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.284946Z

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Observation f05b865a-5dd8-479b-aee0-9e2f15015a0b · outbound

This paper cites Willman, Stan G.

Ascend to Science: Exploration of AI Chips for Scientific Computing Willman, Stan G

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.375672Z

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Observation dbf2aa21-bfe9-4363-bc55-0e6a0558b8ef · outbound

This paper cites Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms.

Ascend to Science: Exploration of AI Chips for Scientific Computing Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.475842Z

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Observation cde1bc64-b3d8-416b-af77-693ab5eb9119 · outbound

This paper cites Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size.

Ascend to Science: Exploration of AI Chips for Scientific Computing Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.569672Z

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Observation ed9344f2-28f9-4c13-8608-9ccf444c122f · outbound

This paper cites 29-billion atoms molecular dynamics simulation with ab initio accuracy on 35 million cores of new sunway supercomputer.IEEE Transactions on Computers, pages 1–14, 2025.

Ascend to Science: Exploration of AI Chips for Scientific Computing 29-billion atoms molecular dynamics simulation with ab initio accuracy on 35 million cores of new sunway supercomputer.IEEE Transactions on Computers, pages 1–14, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:32.678937Z

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Observation 147f1eea-51a5-4639-9f7c-4f4c58991edb · outbound

This paper cites an unresolved cited work.

Ascend to Science: Exploration of AI Chips for Scientific Computing Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-01T10:49:26.837486Z

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