On the other hand, if you’re running two programs which compete for the same function units, there is no advantage at all to having both running “concurrently.” When one is running, the other is necessarily waiting on the same function units.Ī dual core processor literally has two times as many function units as a single-core processor, and can really run two programs concurrently, with no competition for function units.Ī dual core processor is built so that both cores share the same level 2 cache. It just has two execution contexts, so it can maybe achieve better function unit utilization by letting more than one program execute concurrently. You can follow him on Understanding /proc/cpuinfoĪ hyperthreaded processor has the same number of function units as an older, non-hyperthreaded processor. He runs a community Slack of 8300+ members and has over 23,000 followers over LinkedIn. He is a founder of Collabnix blogging site and has authored more than 500+ blogs on Docker, Kubernetes and Cloud-Native Technology. Type Rep CPU = D1 (' MetaData "CPU" "System.CPU" "cpuinfo-0.1.0.Ajeet Raina Follow Ajeet Singh Raina is a Docker Captain, Community Leader and Arm Ambassador. ( Data d, Data e) => c (t d e)) -> Maybe (c CPU) # Data d => c (t d)) -> Maybe (c CPU) #ĭataCast2 :: Typeable t => ( forall d e. r -> c r) -> Constr -> c CPU #ĭataCast1 :: Typeable t => ( forall d. Data b => c (b -> r) -> c r) -> ( forall r. ![]() ![]() Data d => c (d -> b) -> d -> c b) -> ( forall g. Module is unable to provide information on your system please file a bug With a kernel from the 2.6 branch or later by reading /proc/cpuinfo. In its current state this module can only collect information from Linux systems True of numerical workloads, but as always benchmarking should be employed toĮvaluate the impact of different heuristics. There are in fact two logical cores for each physical core. Some workloads mayīenefit from, for example, using half the number of logical cores available if This package allows a program to use information about the physical and logicalįeatures of the available processors as a heuristic for selecting the number of Resources and the thread/spark workloads are similar, then this might be slower However, if each logical core does not have dedicated physical RTS to simply multiplex Haskell threads or sparks over the number of logicalĬores available. It is common for threaded Haskell programs to be run with +RTS -N, causing the Resources are doing the same sort of work there will be scheduling contentionįor a single type of execution resource on the physical core. This is because technologies providing supernumerary logicalĬores typically work by scheduling multiple threads in a shared pool ofĮxecution resources, e.g. Indeed, some parallel workloads may suffer a performance decrease ifĪll logical cores presented by the operating system do not have dedicated ![]() These additional logical cores increase the performance of some, but not all Two logical cores for every physical core present on a supported physical Intel's Hyper-Threading is an example of such a technology, capable of providing Modern hardware provides not only multiple physical processors and physicalĬores, but logical cores which may not have dedicated execution resources. This module provides information about the processors available on a system.
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