Abstract: Emerging applications, e.g., machine learning, large language models (LLMs), and graphic processing, are rapidly developing and are both compute-intensive and memory-intensive. Computing in ...

Element-wise multiplication in Python is a fundamental operation, especially when working with numerical data using libraries like NumPy. Understanding how to perform this efficiently is crucial for ...

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...

Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

Malware disguised as a Python-based trading bot has reportedly targeted crypto traders in a multi-vector supply chain attack. According to a new blog post by cloud-based cybersecurity firm Checkmarx, ...

Matrix multiplication: not supported between 'Matrix' and 'Vector' types #44 Closed lincior opened on May 2, 2024 ...

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