India’s evolving AI landscape still relies largely on GPUs, though the rise of TPU could unfold a huge opportunity for Indian ...

Abstract: Analog computing-in-memory accelerators promise ultra-low-power, on-device AI by reducing data transfer and energy usage. Yet inherent device variations and high energy consumption for ...

Abstract: Nowadays high-performance computing is gradually implementing Exa-scale computing, and the performance of single node has reached several T-flops. Communication problem has become one of the ...

Computational power has become a critical factor in pushing the boundaries of what’s possible in machine learning. As models grow more complex and datasets expand exponentially, traditional CPU-based ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

ABSTRACT: Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale ...