A Survey on Machine Learning Accelerators and Evolutionary Hardware Platforms
Sathwika Bavikadi, Abhijitt Dhavlle, Amlan Ganguly, Anand Haridass, Hagar Hendy, Cory Merkel, Vijay Janapa Reddi, Purab Ranjan Sutradhar, Arun Joseph, Sai Manoj Pudukotai Dinakarrao
Abstract
Advanced computing systems have long been enablers for breakthroughs in artificial intelligence (AI) and machine learning (ML) algorithms, either through sheer computational power or form-factor miniaturization. However, as AI/ML algorithms become more complex and the size of data sets increases, existing computing platforms are no longer sufficient to bridge the gap between algorithmic innovation and hardware design. This article presents a survey about various ML accelerators.
Topics & Concepts
Bridge (graph theory)Computer scienceMiniaturizationComputer architectureArtificial intelligenceMachine learningHyper-heuristicField-programmable gate arrayComputer engineeringEmbedded systemEngineeringElectrical engineeringMobile robotInternal medicineMedicineRobot learningRobotEvolutionary Algorithms and ApplicationsAdvanced Memory and Neural ComputingMetaheuristic Optimization Algorithms Research