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04/14/2023
SpChar: Characterizing the Sparse Puzzle via Decision Trees
Sparse matrix computation is crucial in various modern applications, inc...
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12/13/2022
ALP: Alleviating CPU-Memory Data Movement Overheads in Memory-Centric Systems
Partitioning applications between NDP and host CPU cores causes inter-se...
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11/08/2022
Accelerating Time Series Analysis via Processing using Non-Volatile Memories
Time Series Analysis (TSA) is a critical workload for consumer-facing de...
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10/25/2022
A White-Box Adversarial Attack Against a Digital Twin
Recent research has shown that Machine Learning/Deep Learning (ML/DL) mo...
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06/02/2022
Exploiting Near-Data Processing to Accelerate Time Series Analysis
Time series analysis is a key technique for extracting and predicting ev...
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04/02/2022
Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems
Several manufacturers have already started to commercialize near-bank Pr...
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01/13/2022
SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems
Several manufacturers have already started to commercialize near-bank Pr...
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10/04/2021
Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware
Many modern workloads such as neural network inference and graph process...
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05/09/2021
Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture
Many modern workloads, such as neural networks, databases, and graph pro...
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05/08/2021
DAMOV: A New Methodology and Benchmark Suite for Evaluating Data Movement Bottlenecks
Data movement between the CPU and main memory is a first-order obstacle ...
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01/19/2021
SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures
Near-Data-Processing (NDP) architectures present a promising way to alle...
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10/05/2020