Graphics Processing Units (GPUs) use massive multi-threading coupled with static
scheduling to hide instruction latencies. Despite this, memory instructions pose a challenge …

Analytical models can greatly help computer architects perform orders of magnitude faster
early-stage design space exploration than using cycle-level simulators. To facilitate rapid …

This work explores the interaction of three communication-centric design dimensions for
graph workloads on emerging integrated CPU-GPU systems: update propagation with and …

As GPUs scale their low-precision matrix math throughput to boost deep learning (DL)
performance, they upset the balance between math throughput and memory system …

GPUs are often limited by off-chip memory bandwidth. With the advent of general-purpose
computing on GPUs, a cache hierarchy has been introduced to filter the bandwidth demand …

The widespread adoption of GPUs has driven the development of GPU simulators, which, in
turn, lead advancements in both GPU architectures and software optimization. Trace-driven …

Cycles Per Instruction (CPI) stacks help computer architects gain insight into the
performance of their target architectures and applications. To bring the benefits of CPI stacks …

Molecular electronics saw its birth with the idea to build electronic circuitry with single
molecules as individual components. Even though commercial applications are still modest …

As the benefits from transistor scaling slow down, specialization is becoming increasingly
important for a wide range of applications. Although traditional heterogeneous systems work …

Softwaresimulering er en mye brukt metode for å forske på datamaskin arkitekturer.
Dessverre er det tregt, spesielt for større parallelle arkitekturer, som GPUer. En detaljert …