Abstract: Disclosed herein are systems having an integrated circuit device disposed within an integrated circuit package having a periphery, and within this periphery a transaction processor is configured to receive a combination of signals (e.g., using a standard memory interface), and intercept some of the signals to initiate a data transformation, and forward the other signals to one or more memory controllers within the periphery to execute standard memory access operations (e.g., with a set of DRAM devices). The DRAM devices may or may not be in within the package periphery. In some embodiments, the transaction processor can include a data plane and control plane to decode and route the combination of signals. In other embodiments, off-load engines and processor cores within the periphery can support execution and acceleration of the data transformations.

Abstract: Apparatuses, systems, and techniques to decode encoded data. In at least one embodiment, parts of information for decoding the encoded data is provided to a plurality of processors, and parts of data decoded by the plurality of processors is combined.

Abstract: Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.

Abstract: Disclosed herein are systems having an integrated circuit device disposed within an integrated circuit package having a periphery, and within this periphery a transaction processor is configured to receive a combination of signals (e.g., using a standard memory interface), and intercept some of the signals to initiate a data transformation, and forward the other signals to one or more memory controllers within the periphery to execute standard memory access operations (e.g., with a set of DRAM devices). The DRAM devices may or may not be in within the package periphery. In some embodiments, the transaction processor can include a data plane and control plane to decode and route the combination of signals. In other embodiments, off-load engines and processor cores within the periphery can support execution and acceleration of the data transformations.

Abstract: In various examples, motifs, watermarks, and/or signature inputs are applied to a deep neural network (DNN) to detect faults in underlying hardware and/or software executing the DNN. Information corresponding to the motifs, watermarks, and/or signatures may be compared to the outputs of the DNN generated using the motifs, watermarks and/or signatures. When a the accuracy of the predictions are below a threshold, or do not correspond to the expected predictions of the DNN, the hardware and/or software may be determined to have a fault—such as a transient, an intermittent, or a permanent fault. Where a fault is determined, portions of the system that rely on the computations of the DNN may be shut down, or redundant systems may be used in place of the primary system. Where no fault is determined, the computations of the DNN may be relied upon by the system.

Abstract: In various examples, motifs, watermarks, and/or signature inputs are applied to a deep neural network (DNN) to detect faults in underlying hardware and/or software executing the DNN. Information corresponding to the motifs, watermarks, and/or signatures may be compared to the outputs of the DNN generated using the motifs, watermarks and/or signatures. When a the accuracy of the predictions are below a threshold, or do not correspond to the expected predictions of the DNN, the hardware and/or software may be determined to have a fault—such as a transient, an intermittent, or a permanent fault. Where a fault is determined, portions of the system that rely on the computations of the DNN may be shut down, or redundant systems may be used in place of the primary system. Where no fault is determined, the computations of the DNN may be relied upon by the system.

Abstract: Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.

Abstract: Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.

Abstract: An autonomous driving system could create or exacerbate a hazardous driving situation due to incorrect machine learning, algorithm design, sensor limitations, environmental conditions or other factors. This technology presents solutions that use machine learning to detect when the autonomous driving system is in this state e.g., erratic or reckless driving and other behavior, in order to take remedial action to prevent a hazard such as a collision.

Abstract: An autonomous driving system could create or exacerbate a hazardous driving situation due to incorrect machine learning, algorithm design, sensor limitations, environmental conditions or other factors. This technology presents solutions that use machine learning to detect when the autonomous driving system is in this state e.g., erratic or reckless driving and other behavior, in order to take remedial action to prevent a hazard such as a collision.

Abstract: Apparatuses, systems, and techniques to perform bit matrix multiply and accumulate operations. In at least one embodiment, a Galois residue is determined in response to performing a bit matrix multiply and accumulate operation.

Abstract: In various examples, motifs, watermarks, and/or signature inputs are applied to a deep neural network (DNN) to detect faults in underlying hardware and/or software executing the DNN. Information corresponding to the motifs, watermarks, and/or signatures may be compared to the outputs of the DNN generated using the motifs, watermarks and/or signatures. When a the accuracy of the predictions are below a threshold, or do not correspond to the expected predictions of the DNN, the hardware and/or software may be determined to have a fault—such as a transient, an intermittent, or a permanent fault. Where a fault is determined, portions of the system that rely on the computations of the DNN may be shut down, or redundant systems may be used in place of the primary system. Where no fault is determined, the computations of the DNN may be relied upon by the system.

Abstract: Apparatuses, systems, and techniques to decode encoded data. In at least one embodiment, parts of information for decoding the encoded data is provided to a plurality of processors, and parts of data decoded by the plurality of processors is combined.

Abstract: Often there are errors when reading data from computer memory. To detect and correct these errors, there are multiple types of error correction codes. Disclosed is an error correction architecture that creates a codeword having a data portion and an error correction code portion. Swizzling rearranges the order of bits and distributes the bits among different codewords. Because the data is redistributed, a potential memory error of up to N contiguous bits, where N for example equals 2 times the number of codewords swizzled together, only affects up to, at most, two bits per swizzled codeword. This keeps the error within the error detecting capabilities of the error correction architecture. Furthermore, this can allow improved error correction and detection without requiring a change to error correcting code generators and checkers.

Abstract: An autonomous driving system could create or exacerbate a hazardous driving situation due to incorrect machine learning, algorithm design, sensor limitations, environmental conditions or other factors. This technology presents solutions that use machine learning to detect when the autonomous driving system is in this state e.g., erratic or reckless driving and other behavior, in order to take remedial action to prevent a hazard such as a collision.

Abstract: Disclosed herein are systems having an integrated circuit device disposed within an integrated circuit package having a periphery, and within this periphery a transaction processor is configured to receive a combination of signals (e.g., using a standard memory interface), and intercept some of the signals to initiate a data transformation, and forward the other signals to one or more memory controllers within the periphery to execute standard memory access operations (e.g., with a set of DRAM devices). The DRAM devices may or may not be in within the package periphery. In some embodiments, the transaction processor can include a data plane and control plane to decode and route the combination of signals. In other embodiments, off-load engines and processor cores within the periphery can support execution and acceleration of the data transformations.

Abstract: Disclosed herein are systems having an integrated circuit device disposed within an integrated circuit package having a periphery, and within this periphery a transaction processor is configured to receive a combination of signals (e.g., using a standard memory interface), and intercept some of the signals to initiate a data transformation, and forward the other signals to one or more memory controllers within the periphery to execute standard memory access operations (e.g., with a set of DRAM devices). The DRAM devices may or may not be in within the package periphery. In some embodiments, the transaction processor can include a data plane and control plane to decode and route the combination of signals. In other embodiments, off-load engines and processor cores within the periphery can support execution and acceleration of the data transformations.

Abstract: A memory interface device comprising an address match table. The address match table includes a content entry input and a plurality of hash functions numbered from 1 through N, where N is an integer greater than 1. The address match table includes a first table comprising a plurality of lists numbered from 1 through N, each hash function (i) corresponds to a list (i), where (i) is a number in a set from 1 through N, and a second table coupled to the first table, the second table comprising a plurality of entries, each of the entries point to a different entry within the second table or a null entry in the second table. The interface device includes an index from list N in the first table points to the second table.

Abstract: A method of manufacturing a dynamic random access memory device is provided. The method includes testing a DRAM device using a testing process. The method includes identifying, under control by a computing device, a plurality of bad memory cells from the DRAM device and determining a list of addresses associated with the plurality of bad memory cells. The method includes sorting the list of addresses in either ascending or descending order and subjecting the information from the sorted list of address to a compression process, under control by the computing device, to provide a compressed format including a first content entry in the sorted list and a series of off-set values as provided by a recurrence relationship. The method also stores the compressed format into a non-volatile memory.

Abstract: An error locator unit for correcting two bit error. The error locator unit includes a plurality of operational units, a normalized basis transform unit, and a conversion unit. The plurality of operations units calculates coefficients of the polynomial based on the generated syndromes in a first basis of a Galois Field. Operating on the coefficients produces a root definition value vector in the first basis. The normalized basis transform unit transforms the root definition value vector to a normal basis to produce a plurality of roots. The conversion unit converts the plurality of roots to the first basis. A scaling factor calculated based on the coefficients is applied to the output of the conversion unit to produce a plurality of scaled roots for said polynomial in the first basis. The plurality of scaled roots is added to produce error locations for the polynomial.