najafi
Improved Data Encoding for Emerging Computing Paradigms: From Stochastic to Hyperdimensional Computing
Moghadam, Mehran Shoushtari, Aygun, Sercan, Najafi, M. Hassan
Data encoding is a fundamental step in emerging computing paradigms, particularly in stochastic computing (SC) and hyperdimensional computing (HDC), where it plays a crucial role in determining the overall system performance and hardware cost efficiency. This study presents an advanced encoding strategy that leverages a hardware-friendly class of low-discrepancy (LD) sequences, specifically powers-of-2 bases of Van der Corput (VDC) sequences (VDC-2^n), as sources for random number generation. Our approach significantly enhances the accuracy and efficiency of SC and HDC systems by addressing challenges associated with randomness. By employing LD sequences, we improve correlation properties and reduce hardware complexity. Experimental results demonstrate significant improvements in accuracy and energy savings for SC and HDC systems. Our solution provides a robust framework for integrating SC and HDC in resource-constrained environments, paving the way for efficient and scalable AI implementations.
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How AI simplifies data management for drug discovery
Calithera is running registered clinical trials on its products to study their safety, whether they're effective in patients with specific gene mutations, and how well they work in combination with other therapies. The company must collect detailed data on hundreds of patients. While some of its trials are in early stages and involve only a small number of patients, others span more than 100 research centers across the globe. "In the life-sciences world, one of the biggest challenges we have is the enormous amount of data we generate, more than any other business," says Behrooz Najafi, Calithera's lead information technology strategist. Calithera must store and manage the data while making sure it's readily available when needed, even years from now.
How AI simplifies data management for drug discovery
Calithera is running registered clinical trials on its products to study their safety, whether they're effective in patients with specific gene mutations, and how well they work in combination with other therapies. The company must collect detailed data on hundreds of patients. While some of its trials are in early stages and involve only a small number of patients, others span more than 100 research centers across the globe. "In the life-sciences world, one of the biggest challenges we have is the enormous amount of data we generate, more than any other business," says Behrooz Najafi, Calithera's lead information technology strategist. Calithera must store and manage the data while making sure it's readily available when needed, even years from now.