International Business Machines Corporation

Matthias D Heizmann

Jatin Bhartia

Brian Robert Prasky

James J Bonanno

Narasimha R Adiga

Akash V Giri

Michael J Cadigan, Jr

Daniel Lipetz

Parminder Singh

Ajit S Honnungar

Adam B Collura

Embodiments relate to branch prediction using a pattern history table (PHT) that is indexed using a global path vector (GPV). An aspect includes receiving a search address by a branch prediction logic that is in communication with the PHT and the GPV. Another aspect includes starting with the search address, simultaneously determining a plurality of branch predictions by the branch prediction logic based on the PHT, wherein the plurality of branch predictions comprises one of: (i) at least one not taken prediction and a single taken prediction, and (ii) a plurality of not taken predictions. Another aspect includes updating the GPV by shifting an instruction identifier of a branch instruction associated with a taken prediction into the GPV, wherein the GPV is not updated based on any not taken prediction.

Branch prediction using multi-way pattern history table (PHT) and global path vector (GPV)

Embodiments include a method for verifying a counter design within a tolerance window within which a race condition occurs between a context event and a design event. The method includes receiving a plurality of events within the counter design, the plurality of events including the context event and the design event. The method also includes dynamically determining the tolerance window around the context event by setting a first portion of the tolerance window to precede an occurrence of the context event and by setting a second portion of the tolerance window to follow the context event. Additionally, the method includes performing a verification of whether the design event is within the first portion of the tolerance window or the second portion of the tolerance window.

Robust and adaptable management of event counters

A method comprises identifying a number of branches (N) and a number of iterations (N) in a loop in an instruction stream, generating a number of forward branches until the number of forward branches equals N, generating a non-branch instruction in between the forward branch instruction, recording in a memory, instruction stream generated and a history of each branch, an associated target address of each branch, and whether the branch is a taken branch or a not taken branch, determining whether a loop iterator number (i) is less than N&#x2212;1, generating a backward branch with a target address which is greater than or equal to the start address and is lesser than the current address responsive to determining that (i) is less than N, and recording in the memory, a branch instruction of the generated backward branch and the associated target address of the backward branch.

Pattern based branch prediction

According to an aspect, virtualized weight perceptron branch prediction is provided in a processing system. A selection is performed between two or more history values at different positions of a history vector based on a virtualization map value that maps a first selected history value to a first weight of a plurality of weights, where a number of history values in the history vector is greater than a number of the weights. The first selected history value is applied to the first weight in a perceptron branch predictor to determine a first modified virtualized weight. The first modified virtualized weight is summed with a plurality of modified virtualized weights to produce a prediction direction. The prediction direction is output as a branch predictor result to control instruction fetching in a processor of the processing system.

Perceptron branch predictor with virtualized weights

Embodiments relate to testing memory write operations. An aspect includes detecting a first write operation to a set of 'n' divisions in a memory table, and defining a selected set of entries of an optimization checking table corresponding to the set of 'n' divisions of the memory table. The aspect includes determining that at least one selected entry of the selected set of entries is not among an optimal set of entries of the checking table. The aspect further includes determining whether to generate an optimization error or to end an optimization analysis of the first write operation without generating the optimization error by comparing the first time stamps of one or both of the at least one selected entry and one or more optimal entries of the optimal set of entries to a temporal window defined by a predetermined duration.

Testing optimization of microprocessor table functions

According to an aspect, management of auxiliary branch prediction in a processing system including a primary branch predictor and an auxiliary branch predictor is provided. A congruence class of the auxiliary branch predictor is located based on receiving a primary branch predictor misprediction indicator corresponding to a mispredicted target address of the primary branch predictor. An entry is identified in the congruence class having an auxiliary usefulness level set to a least useful level with respect to one or more other entries of the congruence class. Auxiliary data corresponding to the mispredicted target address is installed into the entry. The auxiliary usefulness level of the entry is reset to an initial value based on installing the auxiliary data.

Auxiliary branch prediction with usefulness tracking

Embodiments include a method, system, and computer program product for verifying a counter design. A method includes receiving a plurality of events within the counter design. The plurality of events can include a context event and a design event. The method also includes determining a tolerance window in response to the receiving of the context. The tolerance window is defined around the context event and includes a first portion before an occurrence of the context event and a second portion after the context event. The method further includes performing a verification algorithm to identify whether the design event is within the tolerance window and should be accounted for by a design model counter of the counter design.

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Poughkeepsie, NY, United States of America

Matthias D Heizmann