tag: AI hardware

AI At The Edge: Optimizing AI Algorithms Without Sacrificing Accuracy
By Ron Lowman - 07 Jul, 2022 - Comments: 0

The ultimate measure of success for AI will be how much it increases productivity in our daily lives. However, the industry has huge challenges in evaluating progress. The vast number of AI applications is in constant churn: finding the right algorithm, optimizing the algorithm, and finding the right tools. In addition, complex hardware engineering is rapidly being updated with many different s... » read more

MIT: Stackable AI Chip With Lego-style Design
By Technical Paper Link - 13 Jun, 2022 - Comments: 0

New technical paper titled "Reconfigurable heterogeneous integration using stackable chips with embedded artificial intelligence" from researchers at MIT, along with Harvard University, Tsinghua University, Zhejiang University, and others. Partial Abstract: "Here we report stackable hetero-integrated chips that use optoelectronic device arrays for chip-to-chip communication and neuromorphic... » read more

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:  "Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and energy-efficient hardware accelerators. We study the potential of Analog AI accelerators based on Non-Volatile Memory, in particular Phase Change Memory (PCM), for software-equivalent accurate i... » read more

Accelerating Inference of Convolutional Neural Networks Using In-memory Computing
By Technical Paper Link - 17 Nov, 2021 - Comments: 0

Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of a... » read more

Accelerating Inference of Convolutional Neural Networks Using In-memory Computing
By Technical Paper Link - 09 Nov, 2021 - Comments: 0

Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of an ... » read more

Startup Funding: December 2020
By Jesse Allen - 06 Jan, 2021 - Comments: 1

AI hardware startups were hot in our December startup-funding focus, with two companies landing rounds exceeding $100M and plenty of others seeing investment. Two Chinese EDA companies received funding in a bid to boost the country's semiconductor ecosystem. One company providing control systems for fabs achieved $8M in Series A, and both autonomous driving and electric vehicles pulled in lots ... » read more

5 Predictions For AI Innovation In 2021
By Arun Venkatachar - 22 Dec, 2020 - Comments: 0

By Arun Venkatachar and Stelios Diamantidis Artificial intelligence (AI) has emerged as one of the most important watchwords in all of technology. The once-utopian vision of developing machines that can think and behave like humans is becoming more of a reality as engineering innovations enable the performance required to process and interpret previously unimaginable amounts of data efficien... » read more

The Emergence Of Hardware As A Key Enabler For The Age Of Artificial Intelligence
By Stelios Diamantidis - 13 Aug, 2020 - Comments: 0

Over the past few decades, software has been the engine of innovation for countless applications. From PCs to mobile phones, well-defined hardware platforms and instruction set architectures (ISA) have enabled many important advancements across vertical markets. The emergence of abundant-data computing is changing the software-hardware balance in a dramatic way. Diverse AI applications in fa... » read more

Power/Performance Bits: July 21
By Jesse Allen - 21 Jul, 2020 - Comments: 0

AI hardware Researchers at Purdue University, University of California San Diego, Argonne National Laboratory, University of Louisville, Brookhaven National Laboratory, and University of Iowa developed hardware that can learn skills, offloading some of the energy needed by AI software. "Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circui... » read more

3 Types Of AI Hardware
By Ed Sperling - 20 Jul, 2020 - Comments: 1

As AI chips become more pervasive, three primary approaches are moving to the forefront. Bradley Geden, director of product marketing at Synopsys, looks at how to take advantage of repeatability, what the different flavors look like, the difference between flat and hierarchical design, and what impact black-box arrays have on programmability. » read more

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