Abstract: Techniques for persisting a logical address-to-virtual address table in a solid state storage device are presented. An example method includes receiving a request to write data to a logical block address (LBA) in a memory component of the solid state storage device. The data is written to a location identified by a virtual block address (VBA) in the solid state storage device. The VBA is stored in a rotating dump table in a reserved logical unit of the solid state storage device. A mapping between the LBA and the VBA is stored in a rotating journal table located in the reserved logical unit. The rotating journal table is buffered such that a number of journal entries are stored in a buffer until a threshold number of journal entries are committed to the rotating journal table. A pointer to a current address in the rotating journal is stored in the buffer.

Abstract: Techniques for persisting a logical address-to-virtual address table in a solid state storage device are presented. An example method includes receiving a request to write data to a logical block address (LBA) in a memory component of the solid state storage device. The data is written to a location identified by a virtual block address (VBA) in the solid state storage device. The VBA is stored in a rotating dump table in a reserved logical unit of the solid state storage device. A mapping between the LBA and the VBA is stored in a rotating journal table located in the reserved logical unit. The rotating journal table is buffered such that a number of journal entries are stored in a buffer until a threshold number of journal entries are committed to the rotating journal table. A pointer to a current address in the rotating journal is stored in the buffer.

Abstract: Simulating particle beam interactions includes identifying a set of n functions F1, F2, . . . , Fn corresponding to a plurality of different physical aspects of a particle beam, performing simulations of each Fi using a full physics model, selecting for each Fi a distribution function fi that models relevant behavior and reducing computation of the full physics model for each Fi by replacing Fi with a distribution function fi. The computation reduction includes comparing a set of simulations wherein each fi replaces its respective Fi to determine if relevant behavior is accurately modeled and selecting one of fi or Fi for each n, for a Monte Carlo simulation based on a runtime and accuracy criteria.

Abstract: A method and system are provided. The method includes condensing, by a processor, an original voxel-beamlet matrix stored in a memory device into a reduced dataset for proton beam simulation and therapy. The original voxel-beamlet matrix has a row for each of a plurality of voxels in a three-dimensional patient volume and a column for each of a plurality of radiation beamlets. The condensing step includes determining protobeams to be extracted from the original voxel-beamlet matrix. The protobeams are columns (i) selected from the original voxel-beamlet matrix based on comparisons performed between the columns in the original voxel-beamlet matrix or (ii) created by combining at least some of the columns in the original voxel-beamlet matrix, in a matrix condensing process. The condensing step further includes extracting the protobeams from the original voxel-beamlet matrix. The condensing step also includes storing the protobeams as the reduced dataset in the memory device.

Abstract: A method and system are provided. The method includes condensing, by a processor, an original voxel-beamlet matrix stored in a memory device into a reduced dataset for proton beam simulation and therapy. The original voxel-beamlet matrix has a row for each of a plurality of voxels in a three-dimensional patient volume and a column for each of a plurality of radiation beamlets. The condensing step includes determining protobeams to be extracted from the original voxel-beamlet matrix. The protobeams are columns (i) selected from the original voxel-beamlet matrix based on comparisons performed between the columns in the original voxel-beamlet matrix or (ii) created by combining at least some of the columns in the original voxel-beamlet matrix, in a matrix condensing process. The condensing step further includes extracting the protobeams from the original voxel-beamlet matrix. The condensing step also includes storing the protobeams as the reduced dataset in the memory device.

Abstract: A hardware accelerator receives a request to decompress a data stream that includes multiple deflate blocks and multiple deflate elements compressed according to block-specific compression configuration information. The hardware accelerator identifies a commit point that is based upon an interruption of a first decompression session of the data stream and corresponds to one of the deflate blocks. As such, the hardware accelerator configures a decompression engine based upon the corresponding deflate block's configuration information and, in turn, recommences decompression of the data stream at an input bit location corresponding to the commit point.

Abstract: An approach is provided in which a hardware accelerator receives a request to decompress a data stream that includes multiple deflate blocks and multiple deflate elements compressed according to block-specific compression configuration information. The hardware accelerator identifies a commit point that is based upon an interruption of a first decompression session of the data stream and corresponds to one of the deflate blocks. As such, the hardware accelerator configures a decompression engine based upon the corresponding deflate block's configuration information and, in turn, recommences decompression of the data stream at an input bit location corresponding to the commit point.

Abstract: A hardware accelerator receives a request to decompress a data stream that includes multiple deflate blocks and multiple deflate elements compressed according to block-specific compression configuration information. The hardware accelerator identifies a commit point that is based upon an interruption of a first decompression session of the data stream and corresponds to one of the deflate blocks. As such, the hardware accelerator configures a decompression engine based upon the corresponding deflate block's configuration information and, in turn, recommences decompression of the data stream at an input bit location corresponding to the commit point.

Abstract: Simulating particle beam interactions includes identifying a set of n functions F1, F2, . . . , Fn corresponding to a plurality of different physical aspects of a particle beam, performing simulations of each Fi using a full physics model, selecting for each Fi a distribution function fi that models relevant behavior and reducing computation of the full physics model for each Fi by replacing Fi with a distribution function fi. The computation reduction includes comparing a set of simulations wherein each fi replaces its respective Fi to determine if relevant behavior is accurately modeled and selecting one of fi or Fi for each n, for a Monte Carlo simulation based on a runtime and accuracy criteria.

Abstract: In response to receiving an input string to be compressed, a plurality of diverse lossless compression techniques are applied to the input string to obtain a plurality of compressed strings. The plurality of diverse lossless compression techniques include a template-based compression technique and a non-template-based compression technique. A most compressed string among the plurality of compressed strings is selected. A determination is made regarding whether or not the most compressed string was obtained by application of the template-based compression technique. In response to determining that the most compressed string was obtained by application of the template-based compression technique, the most compressed string is compressed utilizing the non-template-based compression technique to obtain an output string and outputting the output string.

Abstract: In response to receipt of an input string, an attempt is made to identify, in a template store, a closely matching template for use as a compression template. In response to identification of a closely matching template that can be used as a compression template, the input string is compressed into a compressed string by reference to a longest common subsequence compression template. Compressing the input string includes encoding, in a compressed string, an identifier of the compression template, encoding substrings of the input string not having commonality with the compression template of at least a predetermined length as literals, and encoding substrings of the input string having commonality with the compression template of at least the predetermined length as a jump distance without reference to a base location in the compression template. The compressed string is then output.

Abstract: A mechanism is provided for recirculating transactions within a pipeline while reordering outputs. A set of transactions associated with a block of data is received and each transaction in the set of transactions is processed via the pipeline. For each transaction processed via the pipeline, responsive to the transaction exiting the pipeline, a determination is made as to whether the transaction needs further processing. Responsive to the transaction needing further processing, the transaction is re-circulated via the pipeline forming a recirculated transaction.

Abstract: A mechanism is provided for recirculating transactions within a pipeline while reordering outputs. A set of transactions associated with a block of data is received and each transaction in the set of transactions is processed via the pipeline. For each transaction processed via the pipeline, responsive to the transaction exiting the pipeline, a determination is made as to whether the transaction needs further processing. Responsive to the transaction needing further processing, the transaction is re-circulated via the pipeline forming a recirculated transaction.

Abstract: An approach is provided in which a hardware accelerator receives a request to decompress a data stream that includes multiple deflate blocks and multiple deflate elements compressed according to block-specific compression configuration information. The hardware accelerator identifies a commit point that is based upon an interruption of a first decompression session of the data stream and corresponds to one of the deflate blocks. As such, the hardware accelerator configures a decompression engine based upon the corresponding deflate block's configuration information and, in turn, recommences decompression of the data stream at an input bit location corresponding to the commit point.

Abstract: An approach is provided in which in which a decoder pipeline receives a data stream that includes a stream of deflate blocks. The decoder pipeline decodes an end of block symbol included in one of the deflate blocks and identifies a recycle point in the data stream in response to decoding the end of block symbol. In turn, the decoder pipeline recycles pipeline data residing between the end of block symbol and the recycle point.

Abstract: Mechanisms are provided for decoding a variable length encoded data stream. A decoder of a data processing system receives an input line of data. The input line of data is a portion of the variable length encoded data stream. The decoder determines an amount of bit spill over of the input line of data onto a next input line of data. The decoder aligns the input line of data to begin at a symbol boundary based on the determined amount of bit spill over. The decoder tokenizes the aligned input line of data to generate a set of tokens. Each token corresponds to an encoded symbol in the aligned next input line of data. The decoder generates an output word of data based on the set of tokens. The output word of data corresponds to a word of data in the original set of data.

Abstract: Mechanisms are provided for decoding a variable length encoded data stream. A decoder of a data processing system receives an input line of data. The input line of data is a portion of the variable length encoded data stream. The decoder determines an amount of bit spill over of the input line of data onto a next input line of data. The decoder aligns the input line of data to begin at a symbol boundary based on the determined amount of bit spill over. The decoder tokenizes the aligned input line of data to generate a set of tokens. Each token corresponds to an encoded symbol in the aligned next input line of data. The decoder generates an output word of data based on the set of tokens. The output word of data corresponds to a word of data in the original set of data.

Abstract: A mechanism is provided in a data processing system for pipelined compression of multi-byte frames. The mechanism combines a current cycle of data in an input data stream with at least a portion of a next cycle of data in the input data stream to form a frame of data. The mechanism identifies a plurality of matches in a plurality of dictionary memories. Each match matches a portion of a given substring in the frame of data. The mechanism identifies a subset of matches from the plurality of matches that provides a best coverage of the current cycle of data. The mechanism encodes the frame of data into an encoded output data stream.

Abstract: In response to receipt of an input string, an attempt is made to identify, in a template store, a closely matching template for use as a compression template. In response to identification of a closely matching template that can be used as a compression template, the input string is compressed into a compressed string by reference to a longest common subsequence compression template. Compressing the input string includes encoding, in a compressed string, an identifier of the compression template, encoding substrings of the input string not having commonality with the compression template of at least a predetermined length as literals, and encoding substrings of the input string having commonality with the compression template of at least the predetermined length as a jump distance without reference to a base location in the compression template. The compressed string is then output.

Abstract: In response to receipt of an input string, an attempt is made to identify, in a template store, a closely matching template for use as a compression template. In response to identification of a closely matching template that can be used as a compression template, the input string is compressed into a compressed string by reference to a longest common subsequence compression template. Compressing the input string includes encoding, in a compressed string, an identifier of the compression template, encoding substrings of the input string not having commonality with the compression template of at least a predetermined length as literals, and encoding substrings of the input string having commonality with the compression template of at least the predetermined length as a jump distance without reference to a base location in the compression template. The compressed string is then output.