Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to configure at least some of the compute nodes and interconnects in the compute fabric to execute specified code instructions, and to send to the compute fabric multiple threads that each executes the specified code instructions. A compute node among the compute nodes is configured to execute a code instruction for a first thread, and to transfer a result of the code instruction within the fabric, for use as an operand by a second thread, different from the first thread.

Abstract: A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to configure at least some of the compute nodes and interconnects in the compute fabric to execute specified code instructions, and to send to the compute fabric multiple threads that each executes the specified code instructions. A compute node among the compute nodes is configured to execute a code instruction for a first thread, and to transfer a result of the code instruction within the fabric, for use as an operand by a second thread, different from the first thread.

Abstract: A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

Abstract: A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

Abstract: A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to receive a software program represented as a set of interconnected Data-Flow Graphs (DFGs), each DFG specifying code instructions that perform a respective portion of the software program, to schedule execution of the DFGs in time alternation, and, for each DFG being scheduled, to configure at least some of the compute nodes and interconnects in the compute fabric to execute the code instructions specified in the DFG, and send to the compute fabric multiple threads that each executes the code instructions specified in the DFG.

Abstract: A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to receive at least first and second different Data-Flow Graphs (DFGs), each specifying code instructions, and to configure at least some of the compute nodes and interconnects in the compute fabric to concurrently execute the code instructions specified in the first and second DFGs, and send to the compute fabric multiple first threads that execute the code instructions specified in the first DFG and multiple second threads that execute the code instructions specified in the second DFG, thereby causing the compute fabric to execute, at least during a given time interval, both code instructions specified in the first DFG and code instructions specified in the second DFG.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to receive a software program represented as a set of interconnected Data-Flow Graphs (DFGs), each DFG specifying code instructions that perform a respective portion of the software program, to schedule execution of the DFGs in time alternation, and, for each DFG being scheduled, to configure at least some of the compute nodes and interconnects in the compute fabric to execute the code instructions specified in the DFG, and send to the compute fabric multiple threads that each executes the code instructions specified in the DFG.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to receive at least first and second different Data-Flow Graphs (DFGs), each specifying code instructions, and to configure at least some of the compute nodes and interconnects in the compute fabric to concurrently execute the code instructions specified in the first and second DFGs, and send to the compute fabric multiple first threads that execute the code instructions specified in the first DFG and multiple second threads that execute the code instructions specified in the second DFG, thereby causing the compute fabric to execute, at least during a given time interval, both code instructions specified in the first DFG and code instructions specified in the second DFG.

Abstract: A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Abstract: A processor includes a compute fabric and a controller. The compute fabric includes an array of compute nodes and interconnects that configurably connect the compute nodes. The controller is configured to configure at least some of the compute nodes and interconnects in the compute fabric to execute specified code instructions, and to send to the compute fabric multiple threads that each executes the specified code instructions. A compute node among the compute nodes is configured to execute a code instruction for a first thread, and to transfer a result of the code instruction within the fabric, for use as an operand by a second thread, different from the first thread.

Abstract: A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Abstract: A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Abstract: Data access in a storage device managed by a storage controller is carried out by receiving in the storage controller offsets in objects directly from a plurality of requesting entities of a computer system. The computer controls a mapping mechanism operated by the storage controller, wherein the mapping mechanism relates the offsets in the objects into physical addresses of the data on the storage device, and wherein the data is accessed at the physical addresses.

Abstract: A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Abstract: Data access in a storage device managed by a storage controller is carried out by receiving in the storage controller offsets in objects directly from a plurality of requesting entities of a computer system. The computer controls a mapping mechanism operated by the storage controller, wherein the mapping mechanism relates the offsets in the objects into physical addresses of the data on the storage device, and wherein the data is accessed at the physical addresses.

Abstract: A GPGPU-compatible architecture combines a coarse-grain reconfigurable fabric (CGRF) with a dynamic dataflow execution model to accelerate execution throughput of massively thread-parallel code. The CGRF distributes computation across a fabric of functional units. The compute operations are statically mapped to functional units, and an interconnect is configured to transfer values between functional units.

Abstract: A system and method for performing backfilling on an incoming flow of incoming parallel programs provided by a population of clients to a facility, the system comprising a computer-controlled prediction functionality operative to generate a current run-time prediction for at least some of the incoming parallel programs, a backfiller performing backfilling on the incoming flow of incoming parallel programs based at least partly on at least some of the run-time predictions; and a prediction updater operative, if the current run-time of an incoming parallel program currently in process exceeds the current run-time prediction, to generate an updated run-time prediction to exceed the current run-time, to re-define the current run time to equal the updated run-time prediction, thereby to allow the backfiller to continue performing backfilling based on the updated run-time prediction.