Abstract: In accordance with the described techniques for data compression and decompression for processing in memory, a page address is received by a processing in memory component that maps to a first location in memory where data of a page is maintained. The data of the page is compressed by the processing in memory component. Further, compressed data of the page is written by the processing in memory component to a compressed block device responsive to the compressed data satisfying one or more compressibility criteria. The compressed block device is a portion of the memory dedicated to storing data in a compressed form.

Abstract: A method includes storing a function representing a set of data elements stored in a backing memory and, in response to a first memory read request for a first data element of the set of data elements, calculating a function result representing the first data element based on the function.

Abstract: An electronic device includes one or more data producing nodes and a data consuming node. Each data producing node separately generates two or more portions of a respective block of data. Upon completing generating each portion of the two or more portions of the respective block of data, each data producing node communicates that portion of the respective block of data to the data consuming node. Upon receiving corresponding portions of the respective blocks of data from each of the one or more data producing nodes, the data consuming node performs operations for a model using the corresponding portions of the respective blocks of data.

Abstract: An apparatus configured for offloading system service tasks to a processing-in-memory (“PIM”) device includes an agent configured to: receive, from a host processor, a request to offload a memory task associated with a system service to the PIM device; determine at least one PIM command and at least one memory page associated with the host processor based upon the request; and issue the at least one PIM command to the PIM device for execution by the PIM device to perform the memory task upon the at least one memory page.

Abstract: A method includes storing a function representing a set of data elements stored in a backing memory and, in response to a first memory read request for a first data element of the set of data elements, calculating a function result representing the first data element based on the function.

Abstract: Systems, apparatuses, and methods for implementing memory request priority assignment techniques for parallel processors are disclosed. A system includes at least a parallel processor coupled to a memory subsystem, where the parallel processor includes at least a plurality of compute units for executing wavefronts in lock-step. The parallel processor assigns priorities to memory requests of wavefronts on a per-work-item basis by indexing into a first priority vector, with the index generated based on lane-specific information. If a given event is detected, a second priority vector is generated by applying a given priority promotion vector to the first priority vector. Then, for subsequent wavefronts, memory requests are assigned priorities by indexing into the second priority vector with lane-specific information. The use of priority vectors to assign priorities to memory requests helps to reduce the memory divergence problem experienced by different work-items of a wavefront.

Abstract: Method and apparatus monitor eviction conflicts among cache directory entries in a cache directory and produce cache directory victim entry information for a memory manager. In some examples, the memory manager reduces future cache directory conflicts by changing a page level physical address assignment for a page of memory based on the produced cache directory victim entry information. In some examples, a scalable data fabric includes hardware control logic that performs the monitoring of the eviction conflicts among cache directory entries in the cache directory and produces the cache directory victim entry information.

Abstract: A processing system scales power to memory and memory channels based on identifying causes of stalls of threads of a wavefront. If the cause is other than an outstanding memory request, the processing system throttles power to the memory to save power. If the stall is due to memory stalls for a subset of the memory channels servicing memory access requests for threads of a wavefront, the processing system adjusts power of the memory channels servicing memory access request for the wavefront based on the subset. By boosting power to the subset of channels, the processing system enables the wavefront to complete processing more quickly, resulting in increased processing speed. Conversely, by throttling power to the remainder of channels, the processing system saves power without affecting processing speed.

Abstract: Systems, apparatuses, and methods for implementing memory request priority assignment techniques for parallel processors are disclosed. A system includes at least a parallel processor coupled to a memory subsystem, where the parallel processor includes at least a plurality of compute units for executing wavefronts in lock-step. The parallel processor assigns priorities to memory requests of wavefronts on a per-work-item basis by indexing into a first priority vector, with the index generated based on lane-specific information. If a given event is detected, a second priority vector is generated by applying a given priority promotion vector to the first priority vector. Then, for subsequent wavefronts, memory requests are assigned priorities by indexing into the second priority vector with lane-specific information. The use of priority vectors to assign priorities to memory requests helps to reduce the memory divergence problem experienced by different work-items of a wavefront.

Abstract: A processing device is provided which includes memory and at least one processor. The memory includes main memory and cache memory in communication with the main memory via a link. The at least one processor is configured to receive a request for a cache line and read the cache line from main memory. The at least one processor is also configured to compress the cache line according to a compression algorithm and, when the compressed cache line includes at least one byte predicted not to be accessed, drop the at least one byte from the compressed cache line based on whether the compression algorithm is determined to successfully compress the cache line according to a compression parameter.

Abstract: A processing device is provided which includes memory and at least one processor. The memory includes main memory and cache memory in communication with the main memory via a link. The at least one processor is configured to receive a request for a cache line and read the cache line from main memory. The at least one processor is also configured to compress the cache line according to a compression algorithm and, when the compressed cache line includes at least one byte predicted not to be accessed, drop the at least one byte from the compressed cache line based on whether the compression algorithm is determined to successfully compress the cache line according to a compression parameter.

Abstract: A processing system scales power to memory and memory channels based on identifying causes of stalls of threads of a wavefront. If the cause is other than an outstanding memory request, the processing system throttles power to the memory to save power. If the stall is due to memory stalls for a subset of the memory channels servicing memory access requests for threads of a wavefront, the processing system adjusts power of the memory channels servicing memory access request for the wavefront based on the subset. By boosting power to the subset of channels, the processing system enables the wavefront to complete processing more quickly, resulting in increased processing speed. Conversely, by throttling power to the remainder of channels, the processing system saves power without affecting processing speed.