Processor Architectures/Configuration TRIZ Cases

A graphics processing system applies adaptive prediction methods to generate and transmit frames based on network conditions.

A two-pass graphics processor determines visibility information during a pre-pass to control fragment processing in a main rendering pass.

Radial density masking renders high resolution at fixation points and lower resolution peripherally using subviews.

A BIOS generates a hot-plug detect override request to assert an active-low signal at the graphics display receptacle terminal.

A virtual GPU interaction monitoring system tracks instruction calls between compute instances and graphics servers to enable dynamic resource allocation.

A browser-based video decoder distributes decoding workloads across multiple CPU threads to process independent picture sections in parallel.

Rasterizing source mesh triangles into a voxel grid bakes surface data into target textures, reducing computational cost for massive meshes.

Merges non-overlapping graphics instructions in an instruction buffer to reduce shader switching time and improve GPU rendering efficiency.

A 2D rendering engine calculates light probabilities for distant objects and assigns values to closer ones based on spatial relationships.

Multi-octree data structures enable trilinear interpolation to eliminate artifacts and reduce computational costs in adaptive mesh refinement rendering.

Processing circuitry detects frame rate inadequacy and turns off animation features based on preconfigured values to maintain display fluency.

Eliminates temporary data copies by rearranging points directly in the input buffer, reducing memory requirements for large datasets.

Remote servers aggregate and translate shaders, reducing computational burden on end-user devices.

Cross-linked raster devices generate macro cells via pixel clock stalling to reduce latency and power consumption in video compression.

An image processing apparatus assigns priorities to partial processes based on terminal stage dependencies.

A graphics processing device dynamically selects between a central processing unit and a graphics processing unit to generate screen images.

A meta learning method distributes deep learning model parameters across multiple processing nodes for parallel iterative training.

Segmented interpolation and sampling pipelines use instruction marking to resolve dependencies without costly fence instructions, reducing power consumption.

A low-latency subsystem processes user input signals to generate immediate responses.

Tiled deferred shading segments screen space into tiles to process photon subsets in parallel, reducing computational load while maintaining lighting quality.

Controller selects between first and second image processors based on live view instructions to optimize signal processing paths.

Flattened image chains with token queues allow parallel tile rendering, reducing memory footprint and avoiding disk I/O penalties.

Switching unit routes video signals between internal and external graphics processing units to optimize display output paths.

A reformatting circuit converts raster scan image data into block format for parallel processing by a two-dimensional execution lane array.

Adaptive camera subspace subdivision selects optimal rendering parameters via precomputed Pareto curves.

Transfer protocol logic synchronizes data and clock signals through closely matching routes to eliminate intermediate flip-flops.

A load-balanced tessellation distribution architecture splits high-tessellation-rate patches into sub-patches for parallel processing across multiple geometry and setup pipelines.

Adaptive bounding volumes minimize intersection tests in empty spaces, reducing computational burden during ray traversal.

Dynamic instruction issuance reorders primitives to balance loads across execution units, resolving efficiency versus sequence accuracy trade-offs.

Assigns tessellation factors per point to generate new vertices, preventing cracks between faces with different densities while optimizing bandwidth usage.

A deformation graph embedded with tracked skeleton data animates 3D meshes from human motion.

Segmenting PNG data into index values and color palettes reduces memory usage while improving graphics processing performance on mobile devices.

An offload server analyzes application code to designate GPU processing using OpenACC directives for loop statements.

A LUTDMA engine pre-configures command packets to eliminate interrupt latency during partial frame updates.

A fragment shader groups pixels into variable-precision sets using pilot pixel error thresholds to select processing modes.

Segmented row and column processing circuits reduce power consumption and area usage while maintaining recognition performance on embedded devices.

Segmenting rendering workloads across client and server devices reduces mobile power consumption while maintaining high visual quality.

A GPU server uses a hypervisor to create virtual machines for medical imaging workloads, reducing the need for dedicated computers per cath lab.

Saving and loading GPU kernels enables parallel execution across multiple devices, overcoming limited memory bandwidth between host and device.

A mid-primitive graphics execution preemption method segments the processing pipeline to unload state at execution unit boundaries.

A tile-based immediate mode render pipeline uses a hierarchical visibility structure to sort triangles into screen space tiles for efficient processing.

Pre-computed overlap flags in the tree structure skip non-overlapping nodes, reducing computational time and memory bandwidth.

Segmenting rendering workloads across two graphics processors improves output quality while managing system configuration complexity.

A parameter optimization system restricts data sets to a lower-dimensional affine subspace for efficient surrogate modeling.

Segment original pooling kernels into sub-kernels and store intermediate results in a share line buffer to reduce memory access frequency.

Segmenting shading and blending operations reduces pixel shader resource consumption while maintaining high image quality in super-sampled graphics pipelines.

A CPU-GPU transcoding pipeline maps decoded video to N visual angles and encodes channels for real-time processing.

A tessellation stage maps vertex coordinates to unused parameter space locations for compact binary representation.

A fragment shader executes test instructions to trigger alpha-to-coverage and depth tests during shading.

Segmenting rendering tasks between server and terminal reduces compression artifacts, preserving image fidelity without increasing network latency.