International audienceMost modern processors are heavily parallelized and use predictors to guess the outcome of conditional branches, in order to avoid costly stalls in their pipelines. We propose predictor-friendly versions of two classical algorithms: exponentiation by squaring and binary search in a sorted array. These variants result in less mispredictions on average, at the cost of an increased number of operations. These theoretical results are supported by experimentations that show that our algorithms perform significantly better than the standard ones, for primitive data types. 1998 ACM Subject Classification F.2.2 Nonnumerical Algorithms and Problem
A burgeoning paradigm in algorithm design is the field of algorithms with predictions, in which algo...
In this paper, we introduce a new branch predictor that predicts the outcomes of branches by predict...
Recent implementations of local approximate Gaussian process models have pushed computational bounda...
Most modern processors are heavily parallelized and use predictors to guess the outcome of condition...
International audienceMost modern processors are heavily parallelized and use predictors to guess th...
We explore the fundamental problem of sorting through the lens of learning-augmented algorithms, whe...
A commonly used type of search tree is the alphabetic binary tree, which uses (without loss of gener...
Abstract. The problem of predicting the outcome of a conditional branch instruction is a prerequisit...
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughp...
International audienceLong pipelines need good branch predictors to keep the pipeline running. Curre...
International audienceValue Prediction (VP) is a microarchitectural technique that speculatively bre...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
textPerformance of modern pipelined processor depends on steady flow of useful instructions for proc...
Exploiting the huge computing power of modern microprocessors requires fast, accurate branch predict...
Accurate branch prediction can be seen as a mechanism for enabling design decisions. When short pipe...
A burgeoning paradigm in algorithm design is the field of algorithms with predictions, in which algo...
In this paper, we introduce a new branch predictor that predicts the outcomes of branches by predict...
Recent implementations of local approximate Gaussian process models have pushed computational bounda...
Most modern processors are heavily parallelized and use predictors to guess the outcome of condition...
International audienceMost modern processors are heavily parallelized and use predictors to guess th...
We explore the fundamental problem of sorting through the lens of learning-augmented algorithms, whe...
A commonly used type of search tree is the alphabetic binary tree, which uses (without loss of gener...
Abstract. The problem of predicting the outcome of a conditional branch instruction is a prerequisit...
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughp...
International audienceLong pipelines need good branch predictors to keep the pipeline running. Curre...
International audienceValue Prediction (VP) is a microarchitectural technique that speculatively bre...
This article presents a new and highly accurate method for branch prediction. The key idea is to use...
textPerformance of modern pipelined processor depends on steady flow of useful instructions for proc...
Exploiting the huge computing power of modern microprocessors requires fast, accurate branch predict...
Accurate branch prediction can be seen as a mechanism for enabling design decisions. When short pipe...
A burgeoning paradigm in algorithm design is the field of algorithms with predictions, in which algo...
In this paper, we introduce a new branch predictor that predicts the outcomes of branches by predict...
Recent implementations of local approximate Gaussian process models have pushed computational bounda...