Fully homomorphic encryption (FHE) is an emerging cryptographic technology that
guarantees the privacy of sensitive user data by enabling direct computations on encrypted …

Graphics processing units (GPUs) power today's fastest supercomputers, are the dominant
platform for deep learning, and provide the intelligence for devices ranging from self-driving …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

Modern Graphic Processing Units (GPUs) provide sufficiently flexible programming models
that understanding their performance can provide insight in designing tomorrow's manycore …

High-performance computing has recently seen a surge of interest in heterogeneous
systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices …

In this paper, we present Brook for GPUs, a system for general-purpose computation on
programmable graphics hardware. Brook extends C to include simple data-parallel …

Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are
currently conspiring to create a utilization wall that limits the fraction of a chip that can run at …

In this paper, we introduce the Tensor Streaming Processor (TSP) architecture, a functionally-
sliced microarchitecture with memory units interleaved with vector and matrix deep learning …

Recent advances in graphics processing units (GPUs) have resulted in massively parallel
hardware that is easily programmable and widely available in commodity desktop computer …

We present Sequoia, a programming language designed to facilitate the development of
memory hierarchy aware parallel programs that remain portable across modern machines …