Nvidia was designing graphics processing units GPUs — which, thanks to large numbers of threads and cores, had far higher memory bandwidth than the traditional central processing unit CPUs — as a way to process huge numbers of pixels. That effectively sparked the use of GPUs for general-purpose computing — and, eventually, for massively parallel systems as well.
Believe it or not, the circuit your computer uses to render fancy graphics for video games and 3D animations is built from the same root architecture as the circuits that make possible accurate climate pattern prediction. Wild, huh? The model is a workhorse for medical and commercial applications, too, facilitating everything from drug discovery to interstellar simulations to post-production film techniques.
Here are just a few ways parallel computing is helping improve results and solve the previously unsolvable. Parallel computing is the backbone of other scientific studies, too, including astrophysic simulations, seismic surveying, quantum chromodynamics and more. It can take millions of years for stars to collide, galaxies to merge or black holes to swallow astronomical objects — which is why astrophysicists must turn to computer simulations to study these kinds of processes.
And such complex models demand massive compute power. A recent breakthrough in the study of black holes, for example, happened courtesy of a parallel supercomputer. Researchers solved a four-decade-old mystery, proving that the innermost part of matter that orbits, then collapses into, black holes aligns with those black holes. Seismic data processing has long helped provide a clearer picture of underground strata, an obvious must for industries like oil and gas.
Supercomputing, though, is practically de rigueur in energy excavation nowadays — especially as algorithms process massive amounts of data to help drillers mine difficult terrain, like salt domes. The hope is that by selling parallel power access to third-party companies, fewer energy outfits will feel compelled to build their own, less efficient systems.
Department of Agriculture estimates supply and demand figures for a number of major crops. The crucially important forecasts can impact everyone from legislators striving to stabilize markets to farmers who want to manage their finances.
Their prediction quickly proved more accurate by nearly five bushels per acre. Implementing this type of flexible and intuitive production system brings with it many key benefits including:. The decoupled nature of the IBCs means that you could be formulating a mix in one container, whilst another is being blended, and a third is in the process of being packaged.
The ability to move the IBCs independently around each stage of the manufacturing process creates a much more efficient production line, benefitting from increased capacity. The ability for multiple processes to take place simultaneously means that equipment and operator downtime is greatly reduced.
This reduction is further improved by the ability to fill and clean IBCs whilst they are offline, which entirely eliminates the need for production lines to be put on hold during these processes. In addition, because the IBC is the blending vessel there is no need for blender downtime between batches for cleaning. Mixes remain contained within the sealed IBCs throughout the complete manufacturing process, greatly reducing the risk of cross-contamination.
In contrast, traditional coupled systems often rely on manual handling to transfer ingredients from one process to the next, which creates the potential for contamination to occur. These features provide manufacturers with a system that they can trust to produce consistent products in an efficient and controlled environment, with the added potential to increase capacity to meet consumer demands or manufacture new products.
The Matcon IBC System provides manufacturers with full control over their products at all stages of production. Designed to meet the needs of world-leading manufacturers, the Matcon System employs its unique Cone Valve technology to resolve even the most challenging of powder handling issues.
Cone Valve Technology at the heart of the Matcon system promotes mass product flow by encouraging ingredients at the sides of the IBC to flow, whilst holding back the mix in the centre.
This flow of product allows manufacturers to avoid powder handling issues such as powder segregation or bridging, as well as providing them with full product control during packing, ensuring that the integrity of a product is always consistent.
The simple design of the Matcon IBC means that cleaning is a quick and easy process - containers can be removed from the production line and cleaned in a controlled environment via wet or dry methods. The air wash option removes the risk of any waterborne bacteria growing within your container, whilst the wet wash option can be employed to clean IBCs that have been used for allergens or sticky materials. Implementing a parallel processing system has the potential to greatly increase your manufacturing efficiencies and capabilities.
The Matcon Powder Handling System is a proven manufacturing process that not only employs parallel processing but also provides you with full control over your product at every manufacturing stage, improving consistency and increasing capacity.
Topics: Parallel processing. Implement a flexible manufacturing solution, taking you from start-up to global sports nutrition brand. Need: Develop a more agile system to cope with small batch runs, recipe variety and handle allergens safely. Parallel applications are typically classified as either fine-grained parallelism, in which subtasks will communicate several times per second; coarse-grained parallelism, in which subtasks do not communicate several times per second; or embarrassing parallelism, in which subtasks rarely or never communicate.
Mapping in parallel computing is used to solve embarrassingly parallel problems by applying a simple operation to all elements of a sequence without requiring communication between the subtasks. The popularization and evolution of parallel computing in the 21st century came in response to processor frequency scaling hitting the power wall. Increases in frequency increase the amount of power used in a processor, and scaling the processor frequency is no longer feasible after a certain point; therefore, programmers and manufacturers began designing parallel system software and producing power efficient processors with multiple cores in order to address the issue of power consumption and overheating central processing units.
The importance of parallel computing continues to grow with the increasing usage of multicore processors and GPUs. GPUs work together with CPUs to increase the throughput of data and the number of concurrent calculations within an application. Parallel computer architecture exists in a wide variety of parallel computers, classified according to the level at which the hardware supports parallelism.
Parallel computer architecture and programming techniques work together to effectively utilize these machines. The classes of parallel computer architectures include:. Other parallel computer architectures include specialized parallel computers, cluster computing, grid computing, vector processors, application-specific integrated circuits, general-purpose computing on graphics processing units GPGPU , and reconfigurable computing with field-programmable gate arrays.
Main memory in any parallel computer structure is either distributed memory or shared memory. Concurrent programming languages, APIs, libraries, and parallel programming models have been developed to facilitate parallel computing on parallel hardware.
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