The answer is "money"... In 1999, the "LHC Computing Grid" was merely a concept on the drawing board for a computing system to store, process and analyse data produced from the Large Hadron Collider at CERN. However when work began on the design of the computing system for LHC data analysis, it rapidly became clear that the required computing power was far beyond the funding capacity available at CERN.
The answer is "money"... In 1999, the "LHC Computing Grid" was merely a concept on the drawing board for a computing system to store, process and analyse data produced from the Large Hadron Collider at CERN. However when work began on the design of the computing system for LHC data analysis, it rapidly became clear that the required computing power was far beyond the funding capacity available at CERN.
On the other hand, most of the laboratories and universities collaborating on the LHC had access to national or regional computing facilities.
The obvious question was: Could these facilities be somehow integrated to provide a single LHC computing service? The rapid evolution of wide area networking - increasing capacity and bandwidth coupled with falling costs - made it look possible. From there, the path to the LHC Computing Grid was set.
Multiple copies of data can be kept in different sites, ensuring access for all scientists involved, independent of geographical location
Allows optimum use of spare capacity for multiple computer centres, making it more efficient
Having computer centres in multiple time zones eases round-the-clock monitoring and the availability of expert support
No single points of failure
The cost of maintenance and upgrades is distributed, since individual institutes fund local computing resources and retain responsibility for these, while still contributing to the global goal
Independently managed resources have encouraged novel approaches to computing and analysis
So-called “brain drain”, where researchers are forced to leave their country to access resources, is reduced when resources are available from their desktop
The system can be easily reconfigured to face new challenges, making it able to dynamically evolve throughout the life of the LHC, growing in capacity to meet the rising demands as more data is collected each year
Provides considerable flexibility in deciding how and where to provide future computing resources
Allows community to take advantage of new technologies that may appear and that offer improved usability, cost effectiveness or energy efficiency
Real need for very high performance infrastructures
Basic idea: share distributed computing resources
“The sharing that the GRID is concerned with is not primarily file exchange but rather direct access to computers, software, data, and other resources, as is required by a range of collaborative problem-solving and resource-brokering strategies emerging in industry, science, and engineering” (I. Foster)
Speed-up:
if TS is the best time to process a problem sequentially,
then the parallel processing time should be TP=TS/P with P processors
speedup = TS/TP
the speedup is limited by Amdhal law: any parallel program has a purely sequential and a parallelizable part TS= F + T//,
thus the speedup is limited: S = (F + T//) / (F + (T///P)) < P
Scale-up:
if TPS is the time to solve a problem of size S with P processors,
then TPS should also be the time to process a problem of size n*S with n*P processors
