It has been a long time that computer architecture and systems are optimized for efficient
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …

Computer Architecture: A Quantitative Approach, Fifth Edition, explores the ways that
software and technology in the cloud are accessed by digital media, such as cell phones …

This paper presents a new method for branch prediction. The key idea is to use one of the
simplest possible neural networks, the perceptron, as an alternative to the commonly used …

Efficiently utilizing off-chip DRAM bandwidth is a critical issuein designing cost-effective,
high-performance chip multiprocessors (CMPs). Conventional memory controllers deliver …

In this paper, we have first considered a number of popular recurrent neural network
architectures. Then, two subclasses of general recurrent neural network architectures are …

Tuning compiler optimizations for rapidly evolving hardware makes porting and extending
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …

Compiler writers have crafted many heuristics over the years to approximately solve NP-
hard problems efficiently. Finding a heuristic that performs well on a broad range of …

Compilers base many critical decisions on abstracted architectural models. While recent
research has shown that modeling is effective for some compiler problems, building …

This article presents a new and highly accurate method for branch prediction. The key idea
is to use one of the simplest possible neural methods, the perceptron, as an alternative to …

Writing optimising compilers is difficult. The range of programs that may be presented to the
compiler is huge and the systems on which they run are complex, heterogeneous, non …