Learning and Artificial Intelligence (ML/AI) techniques have become increasingly prevalent
in high performance computing (HPC). However, these methods depend on vast volumes of …

We present BurstZ+, an accelerator platform that eliminates the communication bottleneck
between PCIe-attached scientific computing accelerators and their host servers, via …

Fully Homomorphic Encryption (FHE) is a cryptographic method that guarantees the privacy
and security of user data during computation. FHE algorithms can perform unlimited …

Network compression is now a mature sub-field of neural network research: over the last
decade, significant progress has been made towards reducing the size of models and …

Lossy compression can be an effective tool in AI training and inference to reduce memory
requirements, storage footprint, and in some cases, execution time. With the rise of novel …

In response to the rapidly escalating data movement-related costs of computing with large
matrices and multidimensional arrays, several lossy compression methods have been …

Deep neural networks (DNNs) frequently contain far more weights, represented at a higher
precision, than are required for the specific task which they are trained to perform …

Hardware accelerators such as GPUs and FPGAs can often provide enormous computing
capabilities and power efficiency, as long as the working set fits in the on-board memory …