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Non-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). [ 1 ]
Systems that treat all CPUs equally are called symmetric multiprocessing (SMP) systems. In systems where all CPUs are not equal, system resources may be divided in a number of ways, including asymmetric multiprocessing (ASMP), non-uniform memory access (NUMA) multiprocessing, and clustered multiprocessing.
Diagram of a symmetric multiprocessing system. Symmetric multiprocessing or shared-memory multiprocessing [1] (SMP) involves a multiprocessor computer hardware and software architecture where two or more identical processors are connected to a single, shared main memory, have full access to all input and output devices, and are controlled by a single operating system instance that treats all ...
General schools. According to school year 2017–18 senior secondary school (SMA) statistics from Ministry of Education, [1] in 2017, Indonesia has 13.495 SMA (almost 50-50 ratio between public and private schools) with more than 160 thousand total classrooms (around 12 classrooms per school) and 30 thousands laboratories and 11 thousands libraries, 1,6 million new/10th grade SMA students (45% ...
Uniform memory access (UMA) is a shared memory architecture used in parallel computers.All the processors in the UMA model share the physical memory uniformly. In an UMA architecture, access time to a memory location is independent of which processor makes the request or which memory chip contains the transferred data.
For the 2010–11 season, the Satria Muda ballclub will be fielding two teams for the ABL and the domestic NBL Indonesia, respectively. The team competing in the NBL will be composed of the 2009–10 ABL team, [ 5 ] while the new ABL team is a mixture of new local players, Filipino imports, and American imports.
It is a single UltraSPARC V9 core capable of 4-way SMT. Like the T1, the source code is licensed under the GPL. OpenSPARC T2 , released in 2008, a 64-bit, 64-thread implementation conforming to the UltraSPARC Architecture 2007 and to SPARC Version 9 (Level 1).
The ScyllaDB authors claim that this design allows ScyllaDB to achieve much better performance on modern NUMA SMP machines, and to scale very well with the number of cores. They have measured as much as 2 million requests per second on a single machine, [ 3 ] and also claim that a ScyllaDB cluster can serve as many requests as a Cassandra ...