- X.509 certificates contain a public key and additional metadata (like an
expiration date that AWS verifies when you upload the certificate). Each
certificate is associated with a private key. When you create a request, you
create a digital signature with your private key and then include that
signature in the request, along with your certificate. AWS verifies that
you're the sender by decrypting the signature with the public key that is in
your certificate. AWS also verifies that the certificate you sent matches
the certificate that you uploaded to AWS.
Use X.509 certificates only when you must sign SOAP-based requests. In all other cases, use access keys.
Tensor Parallelism in GPU Tensor parallelism is a technique used to distribute the computation of large tensor operations across multiple GPUs or multiple cores within a GPU . It is an essential method for improving the performance and scalability of deep learning models, particularly when dealing with very large models that cannot fit into the memory of a single GPU. Key Concepts Tensor Operations : Tensors are multidimensional arrays used extensively in deep learning. Common tensor operations include matrix multiplication, convolution, and element-wise operations. Parallelism : Parallelism involves dividing a task into smaller sub-tasks that can be executed simultaneously. This approach leverages the parallel processing capabilities of GPUs to speed up computations. How Tensor Parallelism Works Splitting Tensors : The core idea of tensor parallelism is to split large tensors into smaller chunks that can be processed in parallel. Each chunk is assigned to a different GP...
Comments