Parallelism in hardware is achieved through multiple processors or cores. These processors work together to execute tasks concurrently. Whether it's a multi-core central processing unit (CPU) or a system with m
3. Task parallelism Task parallelism is a type of parallel computing that parallelizes code across several processors simultaneously running tasks on the same data. Task parallelism is used to reduce serial time by running tasks concurrently; in pipelining, for example, where a series of tasks is...
Sparse linear algebra library for exploring fine-grained parallelism on ROCm runtime and toolchains rocBLAS BLAS implementation (in the HIP programming language) on the ROCm runtime and toolchains rocFFT Software library for computing fast Fourier transforms (FFTs) written in HIP ...
Sparse linear algebra library for exploring fine-grained parallelism on ROCm runtime and toolchains rocBLAS BLAS implementation (in the HIP programming language) on the ROCm runtime and toolchains rocFFT Software library for computing fast Fourier transforms (FFTs) written in HIP rocRAND Provides funct...
however multiple cores can share resources such as an l2 cache. multiple cores allow for greater parallelism when executing instructions, meaning that more instructions can be executed simultaneously and therefore more work can be done in less time than with one single-core processor. this makes mul...
However, HPC scenarios use parallelism, too, without using a supercomputer necessarily. Another exception is that supercomputers could use other processor systems, like vector processors, scalar processors or multithreaded processors. Quantum computing is a computing model that harnesses the laws of ...
(NLP). Created by the Applied Deep Learning Research team at NVIDIA, Megatron provides an 8.3 billion parameter transformer language model with 8-way model parallelism and 64-way data parallelism, according toNVIDIA. To execute this model, which is generally pre-trained on a dataset of 3.3 ...
Created by the Applied Deep Learning Research team at NVIDIA, Megatron provides an 8.3 billion parameter transformer language model with 8-way model parallelism and 64-way data parallelism, according to NVIDIA. To execute this model, which is generally pre-trained on a dataset of 3.3 billion ...
Ray and Apache Spark are complementary frameworks. Ray excels at logical parallelism, handling dynamic, compute-intensive tasks like machine learning and reinforcement learning. Apache Spark specializes in data parallelism, efficiently processing large datasets for tasks like ETL and data analytics. Togethe...
Sparse linear algebra library for exploring fine-grained parallelism on ROCm runtime and toolchains rocBLAS BLAS implementation (in the HIP programming language) on the ROCm runtime and toolchains rocFFT Software library for computing fast Fourier transforms (FFTs) written in HIP rocRAND Provides funct...