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New Technique to Reduce Register File Accesses in GPUs

Prof. Nael Ghazaleh and Hodjat Asghari Esfeden from the University of California, Riverside have developed Breathing Operand Windows (BOW), an enhanced GPU pipeline and operand collector technique that supports bypassing register file accesses and instead passes values directly between instructions within the same window. While this baseline design can only bypass register reads, they also introduce an improved design capable of bypassing unnecessary write operations to the RF. Compiler optimizations help guide the write-back destination of operands depending on whether they will be reused to further reduce the write traffic. The BOW microarchitecture reduces RF dynamic energy consumption by 55%, while at the same time increases overall performance by 11%, with a modest overhead of 12KB of additional storage which is ~4% of the RF size. Fig 1: shows the dynamic energy normalized to the baseline GPU for BOW-WR across fifteen different benchmarks. The small segments on top of each bar represent the overheads of the structures added by the idea. Dynamic energy savings in Fig 1 are due to the reduced number of accesses to the register file as BOW-WR shields the RF from unnecessary read and write operations.  

Embedded Power Amplifier

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

System and Method to Improve Human Memory Using a Video Game

Dr. Aaron Seitz and his team have designed multiple tablet-based applications such as Recollect in order to improve memory. Using a video game approach activates cognitive processes while making standard psychological paradigms more engaging. This technology trains participants on various gamified memory tasks where multiple contexts are combined to exercise memory processes in attempt to determine if we might see gains in memory on typical real-world situations. Recollect also offers several built-in assessments aimed at measuring cognitive functions such as working memory, executive functioning, fluid intelligence, and much more. Recollect has been used in children, college students, older adults, and individuals with cognitive deficits (e.g., ADHD, ASD) with the hopes of developing assessments and training programs that are sensitive to the needs of all populations. Fig 1: Image of the working memory training game Recollect.  

Training Technology for Hearing Improvement

Dr. Aaron Seitz and his colleagues from the University of California, Riverside have designed Listen, a tablet-based application developed for the purpose of improving auditory functions. Listen integrates principles of perceptual learning and auditory neuroscience in a reward-based game framework that reinforces program adherence and maintains training efficacy. In the game experience, players find themselves in control of a wisp that must navigate through perilous obstacles by responding appropriately to specific sound cues in order to absorb energy from objects in the environment. Fig 1: Game image from the mobile auditory training application Listen  

Training Technology for Vision Improvement

Dr. Aaron Seitz and his colleagues from the University of California, Riverside have developed a vision tablet-based application that aims to improve sensory and perceptual skills. Sightseeing has been used among a wide variety of populations (e.g., athletes, patients with schizophrenia, children with autism spectrum disorder, college students, and much more). Sensory and perceptual benefits from the application includes observed improvements in visual acuity (i.e., ability to read lower lines on a standard eye chart), contrast sensitivity (i.e., ability to see objects in low light conditions), and peripheral acuity and contrast thresholds. This technology showcases psychophysical designs that enable understanding of mechanisms of perceptual learning and has great potential both as a scientific tool and as therapy to help improve vision.  Fig 1: Contrast sensitivity function. Average CSF on pretest (blue) and posttest (red) for experimental group

Contextual Augmentation Using Scene Graphs

Spatial computing experiences are constrained by the real-world surroundings of the user.  In such experiences, augmenting virtual objects to existing scenes require a contextual approach, where geometrical conflicts are avoided, and functional and plausible relationships to other objects are maintained in the target environment.  Yet, due to the complexity and diversity of user environments, automatically calculating ideal positions of virtual content that is adaptive to the context of the scene is considered a challenging task.    UC researchers have developed a framework which augments scenes with virtual objects using an explicit generative model to learn topological relationship from priors extracted from a real-world and/or synthetic 3D datasets.  Primarily designed for spatial computing applications, SceneGen extracts features from rooms into a novel spatial representation which encapsulates positional and orientational relationships of a scene which captures pairwise topology between objects, object groups, and the room.  The AR application iteratively augments objects by sampling positions and orientations across a room to create a probabilistic heat map of where the object can be placed.  By placing objects in poses where the spatial relationships are likely, we are able to augment scenes that are realistic. 

Virtual Reality For Anhedonia Program

UCLA researchers in the Department of Psychology have developed a behavioral training program for the improvement of anhedonia.

DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM

UCLA researchers in the Department of Mathematicshave developed a method to maintain data privacy.

Machine Learning Program that Diagnoses Hypoadrenocorticism in Dogs Using Standard Blood Test Results

Researchers at the University of California, Davis have developed a program based on machine learning algorithms to aid in diagnosing hypoadrenocorticism.

Development of a CMOS-Compatible, Nano-photonic, Laser

Researchers at the University of California, Davis have developed a new class of lasers and amplifiers that uses a CMOS-compatible electronics platform - and can also be applied to nano-amplifiers and nano-lasers applications.

Deep Learning of Biomimetic Sensorimotor Control for Biomechanical Human Animation

UCLA researchers from the Department of Computer Science have developed a computer simulation model and associated software system for biomimetic human sensorimotor control.

Deep Learning Network and Compression Framework over Limited Bandwidth Network Links

Researchers at the University of California, Davis have developed a technology that enables the quantization of discrete wavelet transformed coefficients to reduce bandwidth for cloud-based storage applications. 

Athermal Nanophotonic Lasers

Researchers at the University of California, Davis have developed a nanolaser platform built from materials that do not exhibit optical gain.

Multi-Wavelength, Nanophotonic, Neural Computing System

Researchers at the University of California, Davis have developed a multi-wavelength, Spiking, Nanophotonic, Neural Reservoir Computing (SNNRC) system with high-dimensional (HD) computing capability.

New Classes Of Cage And Polyhedron And New Classes Of Nanotube And Nanotube With Planar Faces

UCLA researchers have developed a novel algorithm that can be used to design unique self-assembled molecules and nanostructures.

Thermodynamic Integration Simulation Method for Filling Molecular Enclosures Using Spliced Soft-Core Interaction Potential

Researchers have developed a simulation method to determine the properties of molecular enclosures based on slow growth thermodynamic integration (SGTI).

System For Eliminating Clickbaiters On Visual-Centric Social Media

Researchers from the Department of Communication at UCLA have developed a system for identifying and eliminating clickbait from social media.

An Improved On-Chip Crosstalk Noise Model

Researchers led by Jason Cong from the Department of Computer Science at UCLA have developed an improved on-chip crosstalk noise model to optimize integrated circuit design.

A New Human-Monitor Interface For Interpreting Clinical Images

UCLA researchers in the Department of Radiological Sciences have invented a novel interactive tool that can rapidly focus and zoom on a large number of images using eye tracking technology.

Dicom/Pacs Compression Techniques

Researchers led by Xiao Hu from the Department of Surgery at UCLA have created a novel and convenient way to compress and query medical images from a PACS system.

A Method For Discovering And Downloading Hidden Web Content

Researchers in the Computer Science Department at UCLA have developed a method for searching hidden web content that has previously been difficult to gather for the end user.

A New Format For Representing And Encoding Images

Researchers in the Statistics and Computer Science Departments at UCLA have developed a method for image compression that is 5x more efficient than JPEG image coding.

Immersive Virtual Reality To Manage Pain

Researchers led by Mark Cohen from the Department of Psychiatry at UCLA have developed a virtual reality-based therapy to manage chronic pain.

A Device, Methodology And System For Monitoring, Classifying And Encouraging Activity

UCLA researchers in the Department of Computer Science have developed a new technology to fight the growing obesity epidemic by encouraging exercise.

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