Developer Resources from Intel and INESC-ID
INESC-ID gained fast and accurate detection of undiscovered combinations of gene mutations that contribute to complex health conditions and diseases (such as breast cancer or Alzheimer’s disease) using Intel® oneAPI Base Toolkit and Intel® HPC Toolkit on Intel CPUs and GPUs. This research institute also gained:
- Nearly 9x acceleration in epistasis detection using the Cache Aware Roofline Model feature of Intel® Advisor when compared to the baseline implementation.
- Up to 14% better performance on Intel® Data Center GPU Max Series than on an NVIDIA* A100 GPU.
- Up to 52% average performance improvement on Intel® Xeon® CPU Max Series 9480 when compared to the previous generation of Intel CPUs.
Learn More about the INESC-ID Collaboration with Intel
INESC-ID and Intel are working together towards the development and optimization of advanced, scalable bioinformatics code for epistasis detection.
Intel Case Study
INESC-ID achieves 9x acceleration for epistasis disease detection using Intel® tools and hardware.
"With the help of Intel Advisor Cache-Aware Roofline Model, we achieved 8.9x faster execution compared to the baseline implementation for the dataset considered in this study."
— Alexander Ilic, associate professor at Instituto Superior Técnico (IST) and researcher at INESC-ID
Intel® oneAPI Base Toolkit
Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.
Intel® oneAPI HPC Toolkit
Deliver fast applications that scale across clusters with tools and libraries for vectorization, multi-node parallelization, memory optimization, and more.
Download the Stand-Alone Version
Develop performant code quickly and correctly across hardware targets, including CPUs, GPUs, and FPGAs, with this standards-based, multiarchitecture compiler.
Download the Stand-Alone Version
Find and fix performance bottlenecks and optimize application and system performance and configuration for HPC, cloud, IoT, media, storage, and more.
Download the Stand-Alone Version
Design code for efficient vectorization, threading, memory use, and accelerator offload. Supports C, C++, Fortran, SYCL*, OpenMP*, OpenCL™ programs, and Python*.