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Towards Efficient Sparse Matrix Vector Multiplication on Re..:

, In: Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems,

Giannoula, Christina ; Fernandez, Ivan ; Gómez-Luna, Juan... - p. 33-34 , 2022

Link: https://dl.acm.org/doi/10.1145/3489048.3522661

RT 
T1 <cTitle>Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems</cTitle>: T1 <Title>Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3522661&Exemplar=1&LAN=DE
				
A1 Giannoula, Christina
A1 Fernandez, Ivan
A1 Gómez-Luna, Juan
A1 Koziris, Nectarios
A1 Goumas, Georgios
A1 Mutlu, Onur
PB ACM
YR 2022
K1 benchmarking
K1 data movement bottleneck
K1 dram
K1 high-performance computing
K1 memory systems
K1 multicore
K1 near-data processing
K1 processing-in-memory
K1 real-system characterization
K1 sparse matrix-vector multiplication
K1 spmv library
K1 workload characterization
K1 Mathematics of computing
K1 Mathematical analysis
K1 Numerical analysis
K1 Computations on matrices
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Software and its engineering
K1 Software notations and tools
K1 Software libraries and repositories
K1 Computer systems organization
K1 Architectures
K1 Hardware
K1 Integrated circuits
K1 Semiconductor memory
K1 Dynamic memory
K1 Computing methodologies
K1 Modeling and simulation
K1 Model development and analysis
SP 33
OP 34
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3489048.3522661
DO https://dl.acm.org/doi/10.1145/3489048.3522661
SF ELIB - SuUB Bremen

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