Abstract: Methods, systems, and computer program products for queue management are provided. Aspects include receiving a first queue entry and storing the first queue entry in a queue at a first location, wherein the first queue entry includes a first target destination, receiving a second queue entry and storing the second queue entry in the queue at a second location, wherein the second queue entry includes a second target destination, tracking a relative age for each of the first queue entry and the second queue entry, transmitting the first queue entry to the first target destination based at least in part on the relative age for the first queue entry being greater than the relative age for the second queue entry, and receiving a third queue entry and storing the third queue entry in the queue at the first location.

Abstract: Methods, systems, and computer program products for queue management are provided. Aspects include receiving a first queue entry and storing the first queue entry in a queue at a first location, wherein the first queue entry includes a first target destination, receiving a second queue entry and storing the second queue entry in the queue at a second location, wherein the second queue entry includes a second target destination, tracking a relative age for each of the first queue entry and the second queue entry, transmitting the first queue entry to the first target destination based at least in part on the relative age for the first queue entry being greater than the relative age for the second queue entry, and receiving a third queue entry and storing the third queue entry in the queue at the first location.

Abstract: Embodiments are directed to methodologies for efficiently sampling data for analysis by a pipeline analysis algorithm. The amount of sampled data is maximized without increasing sampling overhead by sampling “non-pipeline activity” data if the subject pipeline is inactive during the sampling time. The non-pipeline activity data is selected to include overall system information that is relevant to the subject pipeline's performance but is not necessarily dependent on whether the subject pipeline is active. In some embodiments, the non-pipeline activity data allows for confirmation of a pipeline performance characteristic that must otherwise be inferred by the subsequent pipeline analysis algorithm from data sampled while the pipeline was active. In some embodiments, the non-pipeline activity data allows the pipeline analysis algorithm to analyze additional performance characteristics that cannot otherwise be inferred from the data sampled while the pipeline was active.

Abstract: A method, computer program product, and system for maintaining a proper ordering of a data steam that includes two or more sequentially ordered stores, the data stream being moved to a destination memory device, the two or more sequentially ordered stores including at least a first store and a second store, wherein the first store is rejected by the destination memory device. A computer-implemented method includes sending the first store to the destination memory device. A conditional request is sent to the destination memory device for approval to send the second store to the destination memory device, the conditional request dependent upon successful completion of the first store. The second store is cancelled responsive to receiving a reject response corresponding to the first store.

Abstract: A computer implemented method for avoiding false activation of hang avoidance mechanisms of a system is provided. The computer implemented method includes receiving, by a nest of the system, rejects from a processor core of the system. The rejects are issued based on a cache line being locked by the processor core. The computer implemented method includes accumulating the rejects by the nest. The computer implemented method includes determining, by the nest, when an amount of the rejects accumulated by the nest has met or exceeded a programmable threshold. The computer implemented method also includes triggering, by the nest, a global reset to counters of the hang avoidance mechanisms of a system in response to the amount meeting or exceeding the programmable threshold.

Abstract: Embodiments are directed to systems and methodologies for efficiently sampling data for analysis by a pipeline analysis algorithm. The amount of sampled data is maximized without increasing sampling overhead by sampling “non-pipeline activity” data if the subject pipeline is inactive during the sampling time. The non-pipeline activity data is selected to include overall system information that is relevant to the subject pipeline's performance but is not necessarily dependent on whether the subject pipeline is active. In some embodiments, the non-pipeline activity data allows for confirmation of a pipeline performance characteristic that must otherwise be inferred by the subsequent pipeline analysis algorithm from data sampled while the pipeline was active. In some embodiments, the non-pipeline activity data allows the pipeline analysis algorithm to analyze additional performance characteristics that cannot otherwise be inferred from the data sampled while the pipeline was active.

Abstract: A computer implemented method for avoiding false activation of hang avoidance mechanisms of a system is provided. The computer implemented method includes receiving, by a nest of the system, rejects from a processor core of the system. The rejects are issued based on a cache line being locked by the processor core. The computer implemented method includes accumulating the rejects by the nest. The computer implemented method includes determining, by the nest, when an amount of the rejects accumulated by the nest has met or exceeded a programmable threshold. The computer implemented method also includes triggering, by the nest, a global reset to counters of the hang avoidance mechanisms of a system in response to the amount meeting or exceeding the programmable threshold.

Abstract: A method, computer program product, and system for maintaining a proper ordering of a data steam that includes two or more sequentially ordered stores, the data stream being moved to a destination memory device, the two or more sequentially ordered stores including at least a first store and a second store, wherein the first store is rejected by the destination memory device. A computer-implemented method includes sending the first store to the destination memory device. A conditional request is sent to the destination memory device for approval to send the second store to the destination memory device, the conditional request dependent upon successful completion of the first store. The second store is cancelled responsive to receiving a reject response corresponding to the first store.

Abstract: Maintaining store order with high throughput in a distributed shared memory system. A request is received for a first ordered data store and a coherency check is initiated. A signal is sent that pipelining of a second ordered data store can be initiated. If a delay condition is encountered during the coherency check for the first ordered data store, rejection of the first ordered data store is signaled. If a delay condition is not encountered during the coherency check for the first ordered data store, a signal is sent indicating a readiness to continue pipelining of the second ordered data store.

Abstract: Maintaining store order with high throughput in a distributed shared memory system. A request is received for a first ordered data store and a coherency check is initiated. A signal is sent that pipelining of a second ordered data store can be initiated. If a delay condition is encountered during the coherency check for the first ordered data store, rejection of the first ordered data store is signaled. If a delay condition is not encountered during the coherency check for the first ordered data store, a signal is sent indicating a readiness to continue pipelining of the second ordered data store.

Abstract: A method, computer program product, and system for maintaining a proper ordering of a data steam that includes two or more sequentially ordered stores, the data stream being moved to a destination memory device, the two or more sequentially ordered stores including at least a first store and a second store, wherein the first store is rejected by the destination memory device. A computer-implemented method includes sending the first store to the destination memory device. A conditional request is sent to the destination memory device for approval to send the second store to the destination memory device, the conditional request dependent upon successful completion of the first store. The second store is cancelled responsive to receiving a reject response corresponding to the first store.

Abstract: A method, computer program product, and system for maintaining a proper ordering of a data steam that includes two or more sequentially ordered stores, the data stream being moved to a destination memory device, the two or more sequentially ordered stores including at least a first store and a second store, wherein the first store is rejected by the destination memory device. A computer-implemented method includes sending the first store to the destination memory device. A conditional request is sent to the destination memory device for approval to send the second store to the destination memory device, the conditional request dependent upon successful completion of the first store. The second store is cancelled responsive to receiving a reject response corresponding to the first store.

Abstract: Embodiments relate to matrix and compression-based error detection. An aspect includes summing, by each of a first plurality of summing modules of a first compressor, a respective row of a matrix, the matrix comprising a plurality of rows and a plurality of columns of output bits of a circuit under test wherein each output bit of the circuit under test comprises an element of the matrix, and is a member of a row of a column that is orthogonal to the row. Another aspect includes summing, by each of a second plurality of summing modules of a second compressor, a respective column of output bits of the matrix. Yet another aspect includes determining a presence of an error in the circuit under test based at least one of an output of the first compressor and an output of the second compressor.

Abstract: Embodiments relate to matrix and compression-based error detection. An aspect includes summing, by each of a first plurality of summing modules of a first compressor, a respective row of a matrix, the matrix comprising a plurality of rows and a plurality of columns of output bits of a circuit under test wherein each output bit of the circuit under test comprises an element of the matrix, and is a member of a row of a column that is orthogonal to the row. Another aspect includes summing, by each of a second plurality of summing modules of a second compressor, a respective column of output bits of the matrix. Yet another aspect includes determining a presence of an error in the circuit under test based at least one of an output of the first compressor and an output of the second compressor.

Abstract: Embodiments are directed to systems and methodologies for efficiently sampling data for analysis by a pipeline analysis algorithm. The amount of sampled data is maximized without increasing sampling overhead by sampling “non-pipeline activity” data if the subject pipeline is inactive during the sampling time. The non-pipeline activity data is selected to include overall system information that is relevant to the subject pipeline's performance but is not necessarily dependent on whether the subject pipeline is active. In some embodiments, the non-pipeline activity data allows for confirmation of a pipeline performance characteristic that must otherwise be inferred by the subsequent pipeline analysis algorithm from data sampled while the pipeline was active. In some embodiments, the non-pipeline activity data allows the pipeline analysis algorithm to analyze additional performance characteristics that cannot otherwise be inferred from the data sampled while the pipeline was active.

Abstract: Embodiments relate to matrix and compression-based error detection. An aspect includes summing, by each of a first plurality of summing modules of a first compressor, a respective row of a matrix, the matrix comprising a plurality of rows and a plurality of columns of output bits of a circuit under test wherein each output bit of the circuit under test comprises an element of the matrix, and is a member of a row of a column that is orthogonal to the row. Another aspect includes summing, by each of a second plurality of summing modules of a second compressor, a respective column of output bits of the matrix. Yet another aspect includes determining a presence of an error in the circuit under test based at least one of an output of the first compressor and an output of the second compressor.

Abstract: Embodiments relate to matrix and compression-based error detection. An aspect includes summing, by each of a first plurality of summing modules of a first compressor, a respective row of a matrix, the matrix comprising a plurality of rows and a plurality of columns of output bits of a circuit under test wherein each output bit of the circuit under test comprises an element of the matrix, and is a member of a row of a column that is orthogonal to the row. Another aspect includes summing, by each of a second plurality of summing modules of a second compressor, a respective column of output bits of the matrix. Yet another aspect includes determining a presence of an error in the circuit under test based at least one of an output of the first compressor and an output of the second compressor.

Abstract: Embodiments are directed to methodologies for efficiently sampling data for analysis by a pipeline analysis algorithm. The amount of sampled data is maximized without increasing sampling overhead by sampling “non-pipeline activity” data if the subject pipeline is inactive during the sampling time. The non-pipeline activity data is selected to include overall system information that is relevant to the subject pipeline's performance but is not necessarily dependent on whether the subject pipeline is active. In some embodiments, the non-pipeline activity data allows for confirmation of a pipeline performance characteristic that must otherwise be inferred by the subsequent pipeline analysis algorithm from data sampled while the pipeline was active. In some embodiments, the non-pipeline activity data allows the pipeline analysis algorithm to analyze additional performance characteristics that cannot otherwise be inferred from the data sampled while the pipeline was active.

Abstract: A technique for error detection is provided. A controller is configured to detect errors by using error correcting code (ECC), and a cache includes independent ECC words for storing data. The controller detects the errors in the ECC words for a wordline that is read. The controller detects a first error in a first ECC word on the wordline and a second error in a second ECC word on the wordline. The controller determines that the wordline is a failing wordline based on detecting the first error in the first ECC word and the second error in the second ECC word.

Abstract: A technique for error detection is provided. A controller is configured to detect errors by using error correcting code (ECC), and a cache includes independent ECC words for storing data. The controller detects the errors in the ECC words for a wordline that is read. The controller detects a first error in a first ECC word on the wordline and a second error in a second ECC word on the wordline. The controller determines that the wordline is a failing wordline based on detecting the first error in the first ECC word and the second error in the second ECC word.