Optimizing EDA Cloud Hardware And Workloads


Optimizing EDA hardware for the cloud can shorten the time required for large and complex simulations, but not all workloads will benefit equally, and much more can be done to improve those that can. Tens of thousands of GPUs and specialized accelerators, all working in parallel, add significant and elastic compute horsepower for complex designs. That allows design teams to explore various a... » read more

ISA and Microarchitecture Extensions Over Dense Matrix Engines to Support Flexible Structured Sparsity for CPUs (Georgia Tech, Intel Labs)


A technical paper titled "VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs" was published (preprint) by researchers at Georgia Tech and Intel Labs. Abstract: "Deep Learning (DL) acceleration support in CPUs has recently gained a lot of traction, with several companies (Arm, Intel, IBM) announcing products with specialized matrix engines accessible v... » read more