University of Bristol Accelerates Rational Drug Design
Using Intel TBB, the University of Bristol slashes calculation time for drug development—enabling a calculation that once took 25 days to complete to run in just one day.
Intel TBB: The Backbone of CAD Exchanger Parallelism
Parallelism brings CAD Exchanger software dramatic gains in performance and user satisfaction, plus a competitive advantage. “CAD Exchanger is broadly using multithreaded algorithms to increase performance on multicore systems,” said Roman Lygin of CADEX, Ltd. “This is the key advantage over our competitors.”
Benchmarks show how it outperforms earlier editions in significant ways:
- Some heavyweight computational algorithms, such as blended surface approximation, were accelerated by fifteen times over a single-thread mode.
- Multithreaded visualization significantly increased the responsiveness of the GUI application, which in turn improved the user experience. Less time spent waiting means more time to interact and innovate.
- Parallel file I/O is two and a half times faster and visualization time was reduced by up to four times.
Intel TBB helps Johns Hopkins University Prepare for a Manycore Future
Modern DNA sequencing provides an inexpensive and high-resolution window into diverse aspects of biology, genetics, and disease. Like a microscope, a sequencer produces a snapshot of a collection of cells. Unlike a microscope, a sequencer does not provide a finished, ready-to-interpret image. Rather, it produces billions of tiny snippets (reads) of DNA that must first be composed into longer, interpretable units such as genes or chromosomes. Bowtie and Bowtie 2 are widely used software tools produced in the university’s Langmead Lab that allow biologists to piece together the fragmentary evidence generated by DNA sequencers.
Johns Hopkins and Intel have been collaborating on the Bowtie 2 application. Adding parallelism via Intel TBB resulted in a substantial speedup of the application. By splitting reads from parsing in a critical section, the team saw essentially ideal scaling up to 120 threads.
The team was able to effectively prepare these core genomics software tools for the manycore future around the corner.
Virtual Population Growth: Intel TBB Drives Innovation in Crowd Simulation
“Some years ago, I had to write a library similar to Intel TBB for a cross-platform distributed 3D engine. It took me three months to code and debug the whole thing,” Rouillé said. “With Intel TBB, the guys writing our CPU code provided me with optimized code that I did not have to develop or maintain for critical system services, so I could focus my developers on coding innovations in our key technology.”
Mentor Graphics* Speeds Design Cycles with Intel® Software Tools
Thermal simulations get the performance boost for faster time to market. Mentor Graphics* achieved a significant improvement of nearly two times, even on one core, through code optimization based on the insight provided by Intel® VTune™ Amplifier XE. Good scalability resulted from a combination of Intel TBB and OpenMP* parallelization techniques. More than eight times the performance of the previous version was achieved on eight cores, and up to eleven times the performance on 16 cores. Bottlenecks were overcome in memory allocation with the use of the Intel TBB library. Utilization of the tbb::task concept allowed Mentor Graphics to parallelize complex algorithms in a way that had not been possible with the OpenMP paradigm.
University of Southern California Students Use Intel® Game Development Tools to Increase Game Performance
The University of Southern California (USC) GamePipe Laboratory is part of the USC Viterbi School of Engineering. It is one of the leading game development degree programs in the United States. Midway through the project, the team began to notice performance degradation as more assets were added to the game. Through the use of Intel TBB, an average performance increase of 15 to 20 percent was realized across most test systems, with as much as a 100 percent increase on systems that were particularly CPU-bottlenecked. This resulted in a smoother, more responsive experience as the input handling was now processed synchronously with rendering and combined with higher frame rates, which led to a reduction in input lag.
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