ATI TECHNOLOGIES ULC

Algorithms and hardware implementations within display drivers or associated components to enhance visual quality, resolution, or color reproduction, including upscaling, dithering, and compensation for display artifacts like crosstalk.

Hardware and control techniques for optimizing memory access latency, ensuring data integrity, and managing storage resources efficiently. This includes error correction, read/write voltage control, and intelligent data placement or in-memory computation.

Novel hardware designs and processing pipelines tailored for specific computational tasks, such as graphics rendering, neural network operations, or matrix transformations, often involving custom circuits, memory arrays, or data flow mechanisms.

Methods and apparatus for improving the visual fidelity, resolution, or compression efficiency of video signals, often through advanced processing, up-scaling, or neural network-based filters.

Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.

Techniques and hardware architectures designed to efficiently generate and display complex 3D graphics, particularly for interactive applications like virtual reality, focusing on speed and visual quality.

Methods and systems for improving the quality of video streams, generating intermediate frames, or continuously locating and following objects within a sequence of images, even under occlusion.

Techniques and circuits for optimizing power consumption, voltage stability, and energy efficiency in display panels, often involving dynamic voltage scaling, duty cycle control, or remnant voltage management.

Methods and circuits for coordinating the timing of display signals, data transmission, and control signals across various display components, ensuring proper image rendering and efficient operation.

Technologies enabling the creation and management of virtual computing environments, including virtual machines and virtual desktops, with an emphasis on secure and efficient remote access, updates, and performance.

Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.

Techniques for efficiently supplying power to electronic devices, managing battery charge/discharge cycles, optimizing power consumption, and converting power between different voltage levels or AC/DC for improved energy efficiency and longevity.

Technologies for establishing and managing high-bandwidth, low-latency communication pathways between computing components, peripherals, or systems, focusing on signal integrity, synchronization, and interface standards.

Techniques for stacking multiple semiconductor dies or active layers vertically to achieve higher density and shorter interconnections, often utilizing through-silicon vias (TSVs) or other vertical conductive paths like through-hole electrodes.

Integrated circuits or sub-circuits designed to regulate, balance, or protect power delivery within a device, often involving specific transistor and capacitor arrangements.

Techniques for rendering, interacting with, and managing content within augmented or virtual reality environments, including spatial tracking, gaze interaction, and dynamic multi-application display management.

Technologies that create dynamic and interactive visual content for displays, including virtual/wearable systems, by generating overlays, replacing input streams, or merging real-time user actions with digital environments.

Systems and architectures that enable game execution, content delivery, and interactive social experiences through cloud infrastructure and live streaming technologies.

Packaging technologies where bare dies are embedded within a mold compound or substrate cavity, and then interconnected using redistribution layers (RDLs) for fan-out or compact integration, often avoiding through-silicon vias in the chips themselves.

Technologies that enhance player immersion through advanced graphics rendering, multi-sensory feedback (haptic, auditory), and synchronized interactive experiences in virtual or physical environments.

Novel electrical connection methods within or between package components, including through-glass vias (TGVs), backside contacts, and optimized redistribution layers for improved signal and power integrity.

Design and implementation of circuits and layouts for driving individual pixels or rows/columns of pixels, including gate drivers, data drivers, pixel driving circuits, and their integration onto the display substrate, often in non-display regions.

Techniques for monitoring system components and behaviors to anticipate failures, performance degradation, or anomalies, often leveraging machine learning for pattern recognition and forecasting.

Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.

Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.

Involves systems designed to automatically detect errors or failures and initiate predefined or intelligent corrective actions, recovery procedures, or notifications to minimize downtime and manual intervention.

Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.

Techniques utilizing deep learning models like Generative Adversarial Networks (GANs) or diffusion models to create new images, modify existing ones, or generate synthetic data based on various inputs or conditions.

Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.