There is provided an apparatus including input circuitry that receives input data. Output circuitry outputs a sequence of instructions to be executed by data processing circuitry, at least some of the instructions being grouped into functions and generation circuitry performs a generation process to generate the sequence of instructions using the input data. The generation process causes at least one of the instructions in the sequence of instructions to store a state of control flow speculation performed during execution of the sequence of instructions and the stored state of control flow speculation is maintained between the functions.

There is provided input circuitry to receive input data. Output circuitry outputs a sequence of instructions to be executed by data processing circuitry. Generation circuitry performs a generation process to generate the sequence of instructions using the input data with at least some of the instructions being grouped into functions. The sequence of instructions comprises an indirect control flow instruction comprising a field that indicates where a target of the indirect control flow instruction is stored. The target is an entry point to one of the functions and the generation process causes at least one of the instructions in the sequence of instructions to store a state of control flow speculation after execution of the indirect control flow instruction.

Systems and methods of enabling virtual calls in a single instruction multiple data (SIMD) environment may involve detecting a virtual call of a function and using a single dispatch of the function to invoke the virtual call for two or more channels of the virtual call. In one example, it is determined that the two or more channels share a common target address and a single dispatch of the function is conducted with respect to the common target address. The process may be iterated for additional channels of the virtual call that share a common target address.

The present disclosure includes a mispredict recovery apparatus, which may comprise an instruction execution unit, a branch predictor, and a misprediction recovery unit (MRU). The MRU may provide discrete cycle predictions after a misprediction redirect from the instruction execution unit. The MRU may include a branch confidence filter to generate prediction confidence information for predicted branches. The MRU may include a tag content-addressable memory (CAM). The tag CAM may store frequently mispredicting low-confidence branches, probe the misprediction redirect, and obtain the prediction confidence information from the branch confidence filter. The MRU may include a mispredict recovery buffer (MRB) to store an alternate path for frequently mispredicting low-confidence branches present in the tag CAM without storing the instructions themselves. Also disclosed is a method for recovering from mispredicts associated with the instruction fetch pipeline.

Methods, systems, and apparatus, including an apparatus for processing an instruction for accessing a N-dimensional tensor, the apparatus including multiple tensor index elements and multiple dimension multiplier elements, where each of the dimension multiplier elements has a corresponding tensor index element. The apparatus includes one or more processors configured to obtain an instruction to access a particular element of a N-dimensional tensor, where the N-dimensional tensor has multiple elements arranged across each of the N dimensions, and where N is an integer that is equal to or greater than one; determine, using one or more tensor index elements of the multiple tensor index elements and one or more dimension multiplier elements of the multiple dimension multiplier elements, an address of the particular element; and output data indicating the determined address for accessing the particular element of the N-dimensional tensor.

This application provides an instruction processing method and a chip. The method includes sending, by the thread unit, a search instruction to the search engine unit. The search instruction includes a data address and a first search field, and the thread unit switches from a RUN state to a WAIT state. The method also includes receiving, by the thread unit, data and a program counter that are sent by the search engine unit. The thread unit switches from the WAIT state to the RUN state.

In one embodiment, a processor comprises a decoder to decode a first instruction, the first instruction comprising an opcode and at least one parameter, the opcode to identify the first instruction as an instruction associated with an indirect branch, the at least one parameter indicative of whether the indirect branch is allowed; and circuitry to generate an error message based on the at least one parameter.

Embodiments of this disclosure are directed to an execution profiling handler configured for intercepting an invocation of memory allocation library and observing memory allocation for an executable application process. The observed memory allocation can be used to update memory allocation meta-data for tracking purposes. The execution profiling handler can also intercept indirect branch calls to prevent heap allocation from converting to execution and intercept exploitation of heap memory to block execution.

A system for detecting malware includes a processor to collect processor trace information corresponding to an application being executed by the processor (202). The processor can also detect an invalid indirect branch instruction from the processor trace information (204) and detect at least one malware instruction being executed by the application in response to analyzing modified memory values corresponding to the invalid indirect branch (206). Additionally, the processor can block the application from accessing or modifying memory (208).

Predicting indirect branch instructions may comprise predicting a target address for a fetched branch instruction. Accuracy of the target address may be tracked. The fetched branch instruction may be flagged as a problematic branch instruction based on the tracking. A pattern cache may be trained for predicting a more accurate target address for the fetched branch instruction, and the next time the fetched branch instruction is again fetched, a target address may be predicted from the pattern cache.