Zobrazeno 1 - 10
of 15
pro vyhledávání: '"KALSI, GURPREET S."'
Autor:
Firtina, Can, Pillai, Kamlesh, Kalsi, Gurpreet S., Suresh, Bharathwaj, Cali, Damla Senol, Kim, Jeremie, Shahroodi, Taha, Cavlak, Meryem Banu, Lindegger, Joel, Alser, Mohammed, Luna, Juan Gómez, Subramoney, Sreenivas, Mutlu, Onur
Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequences. In pHMMs, sequences are represented as graph structures. These pr
Externí odkaz:
http://arxiv.org/abs/2207.09765
Autor:
Cali, Damla Senol, Kanellopoulos, Konstantinos, Lindegger, Joel, Bingöl, Zülal, Kalsi, Gurpreet S., Zuo, Ziyi, Firtina, Can, Cavlak, Meryem Banu, Kim, Jeremie, Ghiasi, Nika Mansouri, Singh, Gagandeep, Gómez-Luna, Juan, Alserr, Nour Almadhoun, Alser, Mohammed, Subramoney, Sreenivas, Alkan, Can, Ghose, Saugata, Mutlu, Onur
A critical step of genome sequence analysis is the mapping of sequenced DNA fragments (i.e., reads) collected from an individual to a known linear reference genome sequence (i.e., sequence-to-sequence mapping). Recent works replace the linear referen
Externí odkaz:
http://arxiv.org/abs/2205.05883
Autor:
Kalsi, Gurpreet S., Damelin, Steven B.
For $s$ $>$ 0, we consider an algorithm that computes all $s$-well separated pairs in certain point sets in $\mathbb{R}^{n}$, $n$ $>1$. For an integer $K$ $>1$, we also consider an algorithm that is a permutation of Dijkstra's algorithm, that compute
Externí odkaz:
http://arxiv.org/abs/2103.11216
Autor:
Omer, Om Ji, Laddha, Prashant, Kalsi, Gurpreet S, Thyagharajan, Anirud, Pillai, Kamlesh R, Kulkarni, Abhimanyu, Yao, Anbang, Chen, Yurong, Subramoney, Sreenivas
Semantic understanding and completion of real world scenes is a foundational primitive of 3D Visual perception widely used in high-level applications such as robotics, medical imaging, autonomous driving and navigation. Due to the curse of dimensiona
Externí odkaz:
http://arxiv.org/abs/2011.12669
Autor:
Cali, Damla Senol, Kalsi, Gurpreet S., Bingöl, Zülal, Firtina, Can, Subramanian, Lavanya, Kim, Jeremie S., Ausavarungnirun, Rachata, Alser, Mohammed, Gomez-Luna, Juan, Boroumand, Amirali, Nori, Anant, Scibisz, Allison, Subramoney, Sreenivas, Alkan, Can, Ghose, Saugata, Mutlu, Onur
Genome sequence analysis has enabled significant advancements in medical and scientific areas such as personalized medicine, outbreak tracing, and the understanding of evolution. Unfortunately, it is currently bottlenecked by the computational power
Externí odkaz:
http://arxiv.org/abs/2009.07692
Akademický článek
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Autor:
Kalsi Gurpreet S, Akshay Krishna Ramanathan, Vijaykrishnan Narayanan, Pillai Kamlesh R, Tarun Makesh Chandran, Srivatsa Srinivasa, Sreenivas Subramoney, Omer Om J
Publikováno v:
MICRO
This paper presents a Look-Up Table (LUT) based Processing-In-Memory (PIM) technique with the potential for running Neural Network inference tasks. We implement a bitline computing free technique to avoid frequent bitline accesses to the cache sub-ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f88dc123098275209cf6759e2147a693
https://doi.org/10.1109/micro50266.2020.00020
https://doi.org/10.1109/micro50266.2020.00020
Publikováno v:
ICIP
Many emerging applications of Visual SLAM running on resource constrained hardware platforms impose very aggressive pose accuracy requirements and highly demanding latency constraints. To achieve the required pose accuracy under constrained compute b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66c6b4277dc23c121b23c4fdec44a676
https://doi.org/10.1109/icip40778.2020.9190889
https://doi.org/10.1109/icip40778.2020.9190889
Autor:
Kalsi Gurpreet S, Makesh Chandran, Sahithi Rampalli, Vijaykrishnan Narayanan, Jack Sampson, Sreenivas Subramoney, Nagadastagiri Challapalle
Publikováno v:
DATE
Recurrent Neural Networks (RNNs) are widely used in Natural Language Processing (NLP) applications as they inherently capture contextual information across spatial and temporal dimensions. Compared to other classes of neural networks, RNNs have more
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d076466518400623a0a654d15ed495e
https://doi.org/10.23919/date48585.2020.9116469
https://doi.org/10.23919/date48585.2020.9116469
Autor:
Onur Mutlu, Saugata Ghose, Anant Norion, Damla Senol Cali, Kalsi Gurpreet S, Can Firtina, Sreenivas Subramoneyon, Can Alkan, Mohammed Alser, Juan Gómez-Luna, Jeremie S. Kim, Amirali Boroumand, Rachata Ausavarungnirun, Zülal Bingöl, Allison Scibisz, Lavanya Subramanian
Publikováno v:
Proceedings of the Annual International Symposium on Microarchitecture, MICRO
MICRO
MICRO
Genome sequence analysis has enabled significant advancements in medical and scientific areas such as personalized medicine, outbreak tracing, and the understanding of evolution. Unfortunately, it is currently bottlenecked by the computational power
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca03c6e72bce8f078290000d3bf77053
https://hdl.handle.net/11693/75751
https://hdl.handle.net/11693/75751