Massively parallelMassively parallel is the term for using a large number of computer processors (or separate computers) to simultaneously perform a set of coordinated computations in parallel. GPUs are massively parallel architecture with tens of thousands of threads. One approach is grid computing, where the processing power of many computers in distributed, diverse administrative domains is opportunistically used whenever a computer is available. An example is BOINC, a volunteer-based, opportunistic grid system, whereby the grid provides power only on a best effort basis.
Map (parallel pattern)Map is an idiom in parallel computing where a simple operation is applied to all elements of a sequence, potentially in parallel. It is used to solve embarrassingly parallel problems: those problems that can be decomposed into independent subtasks, requiring no communication/synchronization between the subtasks except a join or barrier at the end. When applying the map pattern, one formulates an elemental function that captures the operation to be performed on a data item that represents a part of the problem, then applies this elemental function in one or more threads of execution, hyperthreads, SIMD lanes or on multiple computers.
Computer performanceIn computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved: Short response time for a given piece of work. High throughput (rate of processing work). Low utilization of computing resource(s). Fast (or highly compact) data compression and decompression.
Non-uniform memory accessNon-uniform memory access (NUMA) is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to the processor. Under NUMA, a processor can access its own local memory faster than non-local memory (memory local to another processor or memory shared between processors). The benefits of NUMA are limited to particular workloads, notably on servers where the data is often associated strongly with certain tasks or users.
Bus snoopingBus snooping or bus sniffing is a scheme by which a coherency controller (snooper) in a cache (a snoopy cache) monitors or snoops the bus transactions, and its goal is to maintain a cache coherency in distributed shared memory systems. This scheme was introduced by Ravishankar and Goodman in 1983, under the name "write-once" cache coherency. A cache containing a coherency controller (snooper) is called a snoopy cache.
Distributed memoryIn computer science, distributed memory refers to a multiprocessor computer system in which each processor has its own private memory. Computational tasks can only operate on local data, and if remote data are required, the computational task must communicate with one or more remote processors. In contrast, a shared memory multiprocessor offers a single memory space used by all processors. Processors do not have to be aware where data resides, except that there may be performance penalties, and that race conditions are to be avoided.
Distributed shared memoryIn computer science, distributed shared memory (DSM) is a form of memory architecture where physically separated memories can be addressed as a single shared address space. The term "shared" does not mean that there is a single centralized memory, but that the address space is shared—i.e., the same physical address on two processors refers to the same location in memory. Distributed global address space (DGAS), is a similar term for a wide class of software and hardware implementations, in which each node of a cluster has access to shared memory in addition to each node's private (i.
Cache control instructionIn computing, a cache control instruction is a hint embedded in the instruction stream of a processor intended to improve the performance of hardware caches, using foreknowledge of the memory access pattern supplied by the programmer or compiler. They may reduce cache pollution, reduce bandwidth requirement, bypass latencies, by providing better control over the working set. Most cache control instructions do not affect the semantics of a program, although some can.
Performance engineeringPerformance engineering encompasses the techniques applied during a systems development life cycle to ensure the non-functional requirements for performance (such as throughput, latency, or memory usage) will be met. It may be alternatively referred to as systems performance engineering within systems engineering, and software performance engineering or application performance engineering within software engineering.
Meltdown (security vulnerability)Meltdown is one of the two original transient execution CPU vulnerabilities (the other being Spectre). Meltdown affects Intel x86 microprocessors, IBM POWER processors, and some ARM-based microprocessors. It allows a rogue process to read all memory, even when it is not authorized to do so. Meltdown affects a wide range of systems. At the time of disclosure (2018), this included all devices running any but the most recent and patched versions of iOS, Linux, macOS, or Windows.
