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Modern distributed systems can benefit from the availability of large-scale and heterogeneous computing infrastructures. However, the complexity and dynamic nature of these environments also call for self-adaptation abilities, as guaranteeing efficient ...

Optimizing the performance of complex systems has always been a central issue for the control theory community. However, ideas and tools from this field often require very precise assumptions and extensive tuning to perform well, making them unsuited ...

A new frontier in human-centered AI is the development of systems that can understand the mental effort of their users in order to better support them in their day-to-day lives. Current solutions rely on specialized sensors to gain insight into a ...

As scaling for CMOS transistors asymptotically approaches the end of Moore's Law, the need to push into 3D integration schemes to innovate capabilities is gaining significant traction. Further, rapid development of new semiconductor solutions, such as ...

Deep learning surrogate models have shown promise in modeling complex physical phenomena such as photonics, fluid flows, molecular dynamics and material properties. However, standard neural networks assume finite-dimensional inputs and outputs, and ...

Spike-based convolutional neural networks (CNNs) are empowered with on-chip learning in their convolution layers, enabling the layer to learn to detect features by combining those extracted in the previous layer. We propose ECHELON, a generalized design ...

Processing-in-memory (PIM) based architecture shows great potential to process several emerging artificial intelligence workloads, including vision and language models. Cross-layer optimizations could bridge the gap between computing density and the ...

Using quantum computing, this paper addresses two scientifically-pressing and day to day-relevant problems, namely, chemical retrosynthesis which is an important step in drug/material discovery and security of semiconductor supply chain. We show that ...

Some of the most significant achievements of the modern era of particle physics, such as the discovery of the Higgs boson, have been made possible by the tremendous effort in building and operating large-scale experiments like the Large Hadron Collider ...

Approximate computing (AxC) has been long accepted as a design alternative for efficient system implementation at the cost of relaxed accuracy requirements. Despite the AxC research activities in various application domains, AxC thrived the past decade ...

Visual saliency computing aims to imitate the human visual attention mechanism to identify the most prominent or unique areas or objects from a visual scene. It is one of the basic low-level image processing techniques and can be applied to many ...

Pixar’s OUT, released summer 2020 on Disney+, is a short film with a highly stylized look, produced under the in-house SparkShorts program. The program champions new creative voices and storytelling via tight-knit production teams that work with ...

Delivering high resolution content is a challenge in the film and games industries due to the cost of photorealistic ray-traced rendering. Image upscaling techniques are commonly used to obtain a high resolution result from a low resolution render. ...

Machine learning techniques have significantly changed our lives. They helped improving our everyday routines, but they also demonstrated to be an extremely helpful tool for more advanced and complex applications. However, the implications of hardware ...

Automating analog layout is a long-standing research problem, with a history that goes back several decades. While digital design is largely automated today, analog layout has been significantly more resistant: automation has not made much headway in ...

The extreme compute requirements of Machine Learning (ML) drives an entirely new generation of hardware. The very compute-intensive ML training is generally done in data centers using re-purposed GPUs. This provides cost-efficient floating-point compute ...

In this invited talk, we discuss state of the art in neural network verification. We propose the term continuous verification to characterise the family of methods that explore continuous nature of machine learning algorithms. We argue that methods of ...

Signs of Life is Griffith Observatory's new 35-minute, 8K, 60fps planetarium show in which we discover what it took to put life in the universe in the one place where we know it exists. In this program we'll discuss how the team was guided by Griffith ...

In Walt Disney Animation Studios’ “Frozen 2”, the Nokk appears as a horse made of water. Throughout the film, he assumes different forms: at times wild, and others calm; above and below the waterline; frozen and transitioning between states. This talk ...

Graph neural networks (GNNs) have received more and more attention in past several years, due to the wide applications of graphs and networks, and the superiority of their performance compared to traditional heuristics-driven approaches. However, most ...