OS-Aware Branch Prediction: Improving Microprocessor Control Flow Prediction for Operating Systems

Li, Qing; John, John; Sivasubramaniam,; Vijaykrishnan,; Rubio,

doi:10.1109/tc.2007.250619

Cited by 5 publications

(5 citation statements)

References 26 publications

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“…The prophet makes prediction based on current branch history and goes on the predicted path, making further predictions which form "branch future" for the original branch. A, Prophet/critic hybrid predictor; B, An example of why critic works Intelligent indexing functions 91 Using multiple indexing functions 50,89 XORing branch address with branch history 84 Converting harmful interference to beneficial or harmless ones 22 Storing only most recent instance of a branch in BP 20 Storing branches with different biases separately 36,83 Separate BPs for user and kernel branches 74 If for a branch B, the prophet makes prediction after observing P extra branches, the number of future bits used by prophet are said to be P, eg, in The critic generates an agree/disagree critique of each prediction of the prophet by correlating with both past and future of a branch.…”

Section: Prophet-critic Hybrid Bpmentioning

confidence: 99%

“…Due to this, it makes more accurate predictions than the prophet. A, Prophet/critic hybrid predictor; B, An example of why critic works 2,30,36,37,65,76,78,91,95 Intelligent indexing functions 91 Using multiple indexing functions 50,89 XORing branch address with branch history 84 Converting harmful interference to beneficial or harmless ones 22 Storing only most recent instance of a branch in BP 20 Storing branches with different biases separately 36,83 Separate BPs for user and kernel branches 74 If for a branch B, the prophet makes prediction after observing P extra branches, the number of future bits used by prophet are said to be P, eg, in should correctly predict more than 90% of branches, and critic is responsible for predicting only the remaining branches. In both traditional hybrid and overriding BPs, component BPs predict the same branch based on the same information; however, in their BP, two predictions happen at different times.…”

Section: Prophet-critic Hybrid Bpmentioning

confidence: 99%

“…Li et al note that branch aliasing between user and kernel codes increases mispredictions in both their executions as their branches show different biases. Also, many branches in kernel mode are weakly biased, and hence, they are difficult to predict by most BPs.…”

Section: Techniques For Improving Bp Accuracymentioning

confidence: 99%

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A survey of techniques for dynamic branch prediction

Mittal

2018

Concurrency and Computation

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Branch predictor (BP) is an essential component in modern processors since high BP accuracy can improve performance and reduce energy by decreasing the number of instructions executed on wrong-path. However, reducing the latency and storage overhead of BP while maintaining high accuracy presents significant challenges. In this paper, we present a survey of dynamic branch prediction techniques. We classify the works based on key features to underscore their differences and similarities. We believe this paper will spark further research in this area and will be useful for computer architects, processor designers, and researchers. KEYWORDSdynamic branch predictor, hybrid BP, neural BP, perceptron predictorside BP, pipelining, predictor accuracy, review, side BP, speculative execution, two-level BP INTRODUCTIONControl-changing instructions such as branches add uncertainty in the execution of dependent instructions and thus lead to large performance loss in pipelined processors. To offset their overhead, accurate prediction of branch outcomes is vital. Since branch misprediction incurs high latency (eg, 14 to 25 cycles 1 ) and wastes energy due to execution of instructions on wrong-path, an improvement in BP* accuracy can boost performance and energy efficiency significantly. For example, experiments on real processors showed that reducing the branch mispredictions by half improved the processor performance by 13%. 2Effective design and management of BPs, however, presents several challenges. Design of BP involves a strict tradeoff between area, energy, accuracy, and latency. An increase in BP complexity for improving accuracy may make it infeasible for implementation or offset its performance benefit. For example, a 512 KB perceptron predictor may provide lower instruction-per-cycle than its 32 KB version, 3 and a 2-cycle fully accurate BP may provide lower instruction-per-cycle than a 1-cycle partially inaccurate BP. 4 Further, due to its high access frequency, BP becomes a thermal hot-spot, 5 and hence, reducing its dynamic and leakage energy is important. Clearly, intelligent techniques are required for resolving these issues.Further, recently, researchers have demonstrated two security vulnerabilities viz., "Meltdown" and "Spectre," which exploit speculative execution feature of modern CPUs. 6-8 For example, Spectre vulnerability works on the observation that the speculative execution due to a branch misprediction may leave side effects, which can reveal sensitive data to attackers, eg, if the memory accesses performed during speculative execution depends on sensitive data, the resulting state of the cache forms a side-channel through which the sensitive data can be leaked. These vulnerabilities affect nearly every modern CPU. While avoiding speculative execution (eg, disabling branch prediction) can mitigate these vulnerabilities, it leads to significant performance loss. In light of these vulnerabilities and associated tradeoffs, a deeper study of branch predictors is definitely required. Contributions:In this ...

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Section: Prophet-critic Hybrid Bpmentioning

confidence: 99%

Section: Prophet-critic Hybrid Bpmentioning

confidence: 99%

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A survey of techniques for dynamic branch prediction

Mittal

2018

Concurrency and Computation

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“…Li et al [71] note that branch aliasing between user/kernel codes increases mispredictions in both their executions as their branches show different biases. Also, many branches in kernel mode are weakly biased which are difficult to predict by most BPs.…”

Section: Reducing Aliasing With Kernel-mode Instructionsmentioning

confidence: 99%

A Survey of Techniques for Dynamic Branch Prediction

Mittal¹

2018

Preprint

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“…There is an additional problem, that the client would have to have some understanding of the code in order to (for example) break code into basic blocks precisely, unless the code is appropriately prepackaged for the client, or the client can use some heuristic instead, like always sending the next N bytes of instructions. A related optimization is branch prediction [38,39], where the server might return extra translated instructions in anticipation of a control flow change.…”

Section: Making Babel Fastermentioning

confidence: 99%

Babel

Aycock

Castro

Locasto

et al. 2012

Proceedings of the 2012 ACM Workshop on Cloud Computing Security Workshop

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Why should a user's computer be trusted at all? We propose a new model of the computer, Babel, that makes a user's computer appear as it normally would, but is actually untrusted to the point where it cannot run the code installed on it. Each computer, each process, speaks a different language, and a translator on the network, in the cloud, is needed to allow a user's computer to execute code. This has enormous implications. The user gets continuous protection, and multiple kinds of protection, with no need for security updates or patches. At the same time, the user effectively has an adjustable control that they can set based on their risk assessment and need for privacy. Babel can work perfectly well alongside existing systems, and opens new markets for security.

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OS-Aware Branch Prediction: Improving Microprocessor Control Flow Prediction for Operating Systems

Cited by 5 publications

References 26 publications

A survey of techniques for dynamic branch prediction

A survey of techniques for dynamic branch prediction

A Survey of Techniques for Dynamic Branch Prediction

Babel

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