Raghavendra Kanakagiri

27 papers A* 2A 4B 2Journal 14Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	ForgetMeNot: Understanding and Modeling the Impact of Forever Chemicals Toward Sustainable Large-Scale Computing. SIGMETRICS (Abstracts) Rohan Basu Roy, Raghavendra Kanakagiri, Yankai Jiang, Devesh Tiwari
2025	J	`jnl`	ForgetMeNot: Understanding and Modeling the Impact of Forever Chemicals Toward Sustainable Large-Scale Computing. CoRR Rohan Basu Roy, Raghavendra Kanakagiri, Yankai Jiang, Devesh Tiwari
2025	J	`jnl`	ForgetMeNot: Understanding and Modeling the Impact of Forever Chemicals Toward Sustainable Large-Scale Computing. Proc. ACM Meas. Anal. Comput. Syst. Rohan Basu Roy, Raghavendra Kanakagiri, Yankai Jiang, Devesh Tiwari
2025	—	`conf`	Parallel Breadth-First Search Optimization Strategies. FCPC@PPOPP Marati Bhaskar, Raghavendra Kanakagiri
2025	J	`jnl`	Performance-Driven Optimization of Parallel Breadth-First Search. CoRR Marati Bhaskar, Raghavendra Kanakagiri
2025	A	`conf`	ThirstyFLOPS: Water Footprint Modeling and Analysis Toward Sustainable HPC Systems. SC Yankai Jiang, Raghavendra Kanakagiri, Rohan Basu Roy, Devesh Tiwari
2025	J	`jnl`	ThirstyFLOPS: Water Footprint Modeling and Analysis Toward Sustainable HPC Systems. CoRR Yankai Jiang, Raghavendra Kanakagiri, Rohan Basu Roy, Devesh Tiwari
2025	B	`conf`	WaterWise: Co-optimizing Carbon- and Water-Footprint Toward Environmentally Sustainable Cloud Computing. PPoPP Yankai Jiang, Rohan Basu Roy, Raghavendra Kanakagiri, Devesh Tiwari
2025	J	`jnl`	WaterWise: Co-optimizing Carbon- and Water-Footprint Toward Environmentally Sustainable Cloud Computing. CoRR Yankai Jiang, Rohan Basu Roy, Raghavendra Kanakagiri, Devesh Tiwari
2024	J	`jnl`	Hardware Acceleration for Knowledge Graph Processing: Challenges & Recent Developments. CoRR Maciej Besta, Robert Gerstenberger, Patrick Iff, Pournima Sonawane, Juan Gómez-Luna, Raghavendra Kanakagiri, Rui Min, Onur Mutlu, Torsten Hoefler, Raja Appuswamy, Aidan O'Mahony
2024	B	`conf`	Minimum Cost Loop Nests for Contraction of a Sparse Tensor with a Tensor Network. SPAA Raghavendra Kanakagiri, Edgar Solomonik
2024	—	`conf`	The Hidden Carbon Footprint of Serverless Computing. SoCC Rohan Basu Roy, Raghavendra Kanakagiri, Yankai Jiang, Devesh Tiwari
2023	A	`conf`	High-Performance and Programmable Attentional Graph Neural Networks with Global Tensor Formulations. SC Maciej Besta, Pawel Renc, Robert Gerstenberger, Paolo Sylos Labini, Alexandros Nikolaos Ziogas, Tiancheng Chen, Lukas Gianinazzi, Florian Scheidl, Kalman Szenes, Armon Carigiet, Patrick Iff, Grzegorz Kwasniewski, Raghavendra Kanakagiri, Chio Ge, Sammy Jaeger, Jaroslaw Was, Flavio Vella, Torsten Hoefler
2023	J	`jnl`	Minimum Cost Loop Nests for Contraction of a Sparse Tensor with a Tensor Network. CoRR Raghavendra Kanakagiri, Edgar Solomonik
2023	—	`conf`	Optimizing Distributed Tensor Contractions Using Node-Aware Processor Grids. Euro-Par Andreas Irmler, Raghavendra Kanakagiri, Sebastian T. Ohlmann, Edgar Solomonik, Andreas Grüneis
2023	J	`jnl`	Optimizing Distributed Tensor Contractions using Node-Aware Processor Grids. CoRR Andreas Irmler, Raghavendra Kanakagiri, Sebastian T. Ohlmann, Edgar Solomonik, Andreas Grüneis
2022	A*	`conf`	Motif Prediction with Graph Neural Networks. KDD Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler
2022	—	`conf`	Parallel Minimum Spanning Forest Computation using Sparse Matrix Kernels. PP Tim Baer, Raghavendra Kanakagiri, Edgar Solomonik
2022	A	`conf`	ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations. SC Maciej Besta, Cesare Miglioli, Paolo Sylos Labini, Jakub Tetek, Patrick Iff, Raghavendra Kanakagiri, Saleh Ashkboos, Kacper Janda, Michal Podstawski, Grzegorz Kwasniewski, Niels Gleinig, Flavio Vella, Onur Mutlu, Torsten Hoefler
2022	J	`jnl`	ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations. CoRR Maciej Besta, Cesare Miglioli, Paolo Sylos Labini, Jakub Tetek, Patrick Iff, Raghavendra Kanakagiri, Saleh Ashkboos, Kacper Janda, Michal Podstawski, Grzegorz Kwasniewski, Niels Gleinig, Flavio Vella, Onur Mutlu, Torsten Hoefler
2021	J	`jnl`	Motif Prediction with Graph Neural Networks. CoRR Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler
2021	J	`jnl`	Parallel Minimum Spanning Forest Computation using Sparse Matrix Kernels. CoRR Tim Baer, Raghavendra Kanakagiri, Edgar Solomonik
2021	A*	`conf`	SISA: Set-Centric Instruction Set Architecture for Graph Mining on Processing-in-Memory Systems. MICRO Maciej Besta, Raghavendra Kanakagiri, Grzegorz Kwasniewski, Rachata Ausavarungnirun, Jakub Beránek, Konstantinos Kanellopoulos, Kacper Janda, Zur Vonarburg-Shmaria, Lukas Gianinazzi, Ioana Stefan, Juan Gómez-Luna, Jakub Golinowski, Marcin Copik, Lukas Kapp-Schwoerer, Salvatore Di Girolamo, Nils Blach, Marek Konieczny, Onur Mutlu, Torsten Hoefler
2021	J	`jnl`	SISA: Set-Centric Instruction Set Architecture for Graph Mining on Processing-in-Memory Systems. CoRR Maciej Besta, Raghavendra Kanakagiri, Grzegorz Kwasniewski, Rachata Ausavarungnirun, Jakub Beránek, Konstantinos Kanellopoulos, Kacper Janda, Zur Vonarburg-Shmaria, Lukas Gianinazzi, Ioana Stefan, Juan Gómez-Luna, Marcin Copik, Lukas Kapp-Schwoerer, Salvatore Di Girolamo, Marek Konieczny, Onur Mutlu, Torsten Hoefler
2020	A	`conf`	Communication-Efficient Jaccard similarity for High-Performance Distributed Genome Comparisons. IPDPS Maciej Besta, Raghavendra Kanakagiri, Harun Mustafa, Mikhail Karasikov, Gunnar Rätsch, Torsten Hoefler, Edgar Solomonik
2019	J	`jnl`	Communication-Efficient Jaccard Similarity for High-Performance Distributed Genome Comparisons. CoRR Maciej Besta, Raghavendra Kanakagiri, Harun Mustafa, Mikhail Karasikov, Gunnar Rätsch, Torsten Hoefler, Edgar Solomonik
2019	J	`jnl`	Scalable GW software for quasiparticle properties using OpenAtom. Comput. Phys. Commun. Minjung Kim, Subhasish Mandal, Eric Mikida, Kavitha Chandrasekar, Eric J. Bohm, Nikhil Jain, Qi Li, Raghavendra Kanakagiri, Glenn J. Martyna, Laxmikant V. Kalé, Sohrab Ismail-Beigi

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.