Abstract:
By packing the depth data in a way that is independent of the number of samples, so that memory bandwidth is the same regardless of the number of samples, higher numbers of samples per pixel may be used without adversely affecting buffer cost. In some embodiments, the number of pixels per clock in a first level depth test may be increased by operating in the pixel domain, whereas previous solutions operated at the sample level.
Abstract:
Techniques related to graphics rendering including techniques for compression and/or decompression of graphics data by use of indexed subsets are described.
Abstract:
Techniques related to graphics rendering including techniques for compression and/or decompression of graphics data by use of pixel region bit values are described.
Abstract:
Methods, systems and apparatuses provide for graphics processor technology that generates attribute plane coefficients based on barycentric coefficients, wherein the attribute plane coefficients are generated on a per polygon basis, and interpolates one or more pixel attributes based on the attribute plane coefficients. In one example, the technology excludes the barycentric coefficients from one or more per pixel operations.
Abstract:
Graphics processors of the present design provide hierarchical open sectors and variable cache sizes for cache operations. In one embodiment, a graphics processor comprises a cache memory having a hierarchical open sector design including a first hierarchy of upper and lower regions with each region including a second hierarchy of sectors. A cache controller is configured to initially open a first sector of the lower region, to receive a memory request that does not match an address in the first sector, and to open a second sector of the lower region.
Abstract:
Embodiments are generally directed to cache structure and utilization. An embodiment of an apparatus includes one or more processors including a graphics processor; a memory for storage of data for processing by the one or more processors; and a cache to cache data from the memory; wherein the apparatus is to provide for dynamic overfetching of cache lines for the cache, including receiving a read request and accessing the cache for the requested data, and upon a miss in the cache, overfetching data from memory or a higher level cache in addition to fetching the requested data, wherein the overfetching of data is based at least in part on a current overfetch boundary, and provides for data is to be prefetched extending to the current overfetch boundary.
Abstract:
Embodiments described herein include, software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. One embodiment provides techniques to optimize training and inference on a systolic array when using sparse data. One embodiment provides techniques to use decompression information when performing sparse compute operations. One embodiment enables the disaggregation of special function compute arrays via a shared reg file. One embodiment enables packed data compress and expand operations on a GPGPU. One embodiment provides techniques to exploit block sparsity within the cache hierarchy of a GPGPU.
Abstract:
Embodiments are generally directed to data prefetching for graphics data processing. An embodiment of an apparatus includes one or more processors including one or more graphics processing units (GPUs); and a plurality of caches to provide storage for the one or more GPUs, the plurality of caches including at least an L1 cache and an L3 cache, wherein the apparatus to provide intelligent prefetching of data by a prefetcher of a first GPU of the one or more GPUs including measuring a hit rate for the L1 cache; upon determining that the hit rate for the L1 cache is equal to or greater than a threshold value, limiting a prefetch of data to storage in the L3 cache, and upon determining that the hit rate for the L1 cache is less than a threshold value, allowing the prefetch of data to the L1 cache.
Abstract:
Embodiments are generally directed to providing power savings for a neural network architecture with zero activations during inference. An embodiment of an apparatus includes one or more processors including one or more processor cores; and a memory to store data for processing including neural network processing, wherein the apparatus to perform a fast clear operation to initialize activation buffers for a neural network by updating metadata to indicate zero values, the neural network including a plurality of layers, wherein the apparatus is to compare outputs for the neural network to the metadata values and to write an output to memory only if the output is non-zero.
Abstract:
Described herein are several embodiments which provide for enhanced data caching in combination with adaptive and dynamic compression to increase the storage efficiency and reduce the transmission bandwidth of data during input and output from a GPU. The techniques described herein can reduce the need to access off-chip memory, resulting in improved performance and reduced power for GPU operations. One embodiment provides for a graphics processing apparatus comprising a shader engine; one or more cache memories; cache control logic to control at least one of the one or more cache memories; and a codec unit coupled with the one or more cache memories, the codec unit configurable to perform lossless compression of read-only surface data upon storage to or eviction from the one or more cache memories.