Techniques are provided herein for more efficiently storing images that have a common subject, such as product images that share the same product in the image. Each image undergoes an adaptive tiling procedure to split the image into a plurality of tiles, with each tile identifying a region of the image having pixels with the same content. The tiles across multiple images can then be clustered together and those tiles having identical content are removed. Once all duplicate tiles have been removed from the set of all tiles across the images, the tiles are once again clustered based on their encoding scheme and certain encoding parameters. Tiles within each cluster are compressed using the best compression technique for the tiles in each corresponding cluster. By removing duplicative tile content between numerous images of the same subject, the total amount of data that needs to be stored is reduced.

Partition information associated with one or more partitions that divide a range of values into at least a higher and lower set of values is received. An uncompressed value that falls within the range of values is received and a compressed value that includes a set indicator and intra-set information is generated using the uncompressed value. This includes generating the set indicator based at least in part on whether the uncompressed value falls in the higher or lower set of values, determining whether the uncompressed value includes an extraneous bit where it is necessary but not sufficient that the uncompressed value fall in the higher set of values for the uncompressed value to include the extraneous bit, and generating the intra-set information, including by: excluding the extraneous bit in the uncompressed value from the intra-set information if it is determined to be included. The compressed value is output.

Methods, systems, and computer programs for compressing nucleic acid sequence data. A method can include obtaining nucleic acid sequence data representing: (i) a read sequence, and (ii) a plurality of quality scores, determining whether the read sequence includes at least one “N” base, based on a determination that the read sequence does not include at least one “N” base, generating a first encoded data set by using a first encoding process to encode each of the quality scores of the read sequence using a base-(x minus 1) number, where x is an integer representing a number of different quality scores used by the nucleic acid sequencing device, and using a second encoding process to encode the first encoded data set, thereby compressing the data to be compressed.

Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

Technologies for generating manifest data for a sled include a sled to generate manifest data indicative of one or more characteristics of the sled (e.g., hardware resources, firmware resources, a configuration of the sled, or a health of sled components). The sled is also to associate an identifier with the manifest data. The identifier uniquely identifies the sled from other sleds. Additionally, the sled is to send the manifest data and the associated identifier to a server. The sled may also detect a change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also generate an update of the manifest data based on the detected change, where the update specifies the detected change in the hardware resources, firmware resources, the configuration, or component health of the sled. The sled may also send the update of the manifest data to the server.

Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

Techniques for generating data sets may include: receiving an initial buffer that achieves a compression ratio responsive to compression processing using a compression algorithm, the initial buffer including first content located at a first position in the initial buffer and including second content located at a second position in the initial buffer; and generating a data set of buffers using the initial buffer. The data set may be expected to achieve a specified deduplication ratio responsive to deduplication processing and to achieve the compression ratio responsive to compression processing using the compression algorithm. Generating the data set may include generating a first plurality of buffers where each buffer of the first plurality is not a duplicate of another buffer in the first plurality, and generating a second plurality of duplicate buffers. Each duplicate buffer may be a duplicate of a buffer in the first plurality of buffers.

An embodiment of the invention may include a method, computer program product and system for saving data received from a host computing device to a storage system. The storage system includes at least one processor and at least one storage. An embodiment may include storing the received data to the storage on a record basis. A record includes a record header including information indicative of an implemented compression method of the record. An embodiment may include monitoring a processing load of the at least one processor. In response to the processing load being less than a predetermined level, an embodiment may include further compressing the record utilizing a high-ratio compression method based on the record requiring further compression. An embodiment may include updating the record header information to reflect details of the utilized a high-ratio compression method. An embodiment may include storing the further compressed record to the storage.

A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. To compress the attribute information, a transform is applied to the attribute values to generate attribute coefficients/transformed attribute values. Points with attribute coefficients with a significant value are assigned a first binary flag value, while points with non-significant attribute coefficients are assigned a second binary flag value. A K.sup.th order exponential Golomb encoder or Golomb-Rice encoder is used to compress the run-length values, where separate states and associated contexts are maintained for funs of both the first and second binary values. A decoder uses a corresponding process to decode the compressed attribute information.

Technologies for dividing work across one or more accelerator devices include a compute device. The compute device is to determine a configuration of each of multiple accelerator devices of the compute device, receive a job to be accelerated from a requester device remote from the compute device, and divide the job into multiple tasks for a parallelization of the multiple tasks among the one or more accelerator devices, as a function of a job analysis of the job and the configuration of each accelerator device. The compute engine is further to schedule the tasks to the one or more accelerator devices based on the job analysis and execute the tasks on the one or more accelerator devices for the parallelization of the multiple tasks to obtain an output of the job.