Lerner, Alberto Hussein, Rana Ryser, André Lee, Sangjin Cudré-Mauroux, Philippe 2020 Many large computer clusters offer alternative computing elements in addition to general-purpose CPUs. GPU and FPGAs are very common choices. Two emerging technologies can further widen the options in that context: in-network computing (INC) and near-storage processing (NSP). These technologies support computing over data that is in transit between nodes or inside the storage stack, respectively. There are several advantages to moving computations to INC and NSP platforms. Notably, the original computation path does not need to be altered to route data through these subsystems; the network and the storage are naturally present in most computations. In this paper, we describe the evolutionary steps that led to INC and NSP platforms and discuss how they can improve critical computing paths in large-scale database systems. In the process, we comment on the constraints that the current generation of these platforms present as well as expose why we believe them to be relevant to the next generation of exascale platforms. application/pdf https://folia.unifr.ch/global/documents/309203 https://folia.unifr.ch/documents/309203/files/2020_Cudre-Mauroux_Networking.pdf eng http://sites.computer.org/debull/A20mar/p60.pdf info:eu-repo/semantics/openAccess License undefined IEEE Data Engineering Bulletin. - 2020, vol. 43, no. 1, p. 60-71 networking storage info:eu-repo/classification/udc/004 Networking and Storage : The Next Computing Elements in Exascale Systems? http://purl.org/coar/resource_type/c_6501