As modern GPUs rely partly on their on-chip memories to counter the imminent off-chip memory wall, the efficient use of their caches has become important for performance and energy. However, optimising cache locality system-atically requires insight into and prediction of cache be-haviour. On sequential processors, stack distance or reuse distance theory is a well-known means to model cache be-haviour. However, it is not straightforward to apply this theory to GPUs, mainly because of the parallel execution model and fine-grained multi-threading. This work extends reuse distance to GPUs by modelling: 1) the GPU’s hier-archy of threads, warps, threadblocks, and sets of active threads, 2) conditional and non-uniform latencies, 3) cache associa...
Graphics Processing Units (GPUs) have been shown to be effective at achieving large speedups over co...
The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly ...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
As modern GPUs rely partly on their on-chip memories to counter the imminent off-chip memory wall, t...
In the present paper, we propose RDGC, a reuse distance-based performance analysis approach for GPU ...
Traditionally, GPUs only had programmer-managed caches. The advent of hardware-managed caches accele...
Analytical performance models yield valuable architectural insight without incurring the excessive r...
As a throughput-oriented device, Graphics Processing Unit(GPU) has already integrated with cache, wh...
Abstract—With the SIMT execution model, GPUs can hide memory latency through massive multithreading ...
The diversity of workloads drives studies to use GPU more effectively to overcome the limited memory...
Graphics processing units (GPUs) have become ubiquitous for general purpose applications due to thei...
Abstract—In a GPU, all threads within a warp execute the same instruction in lockstep. For a memory ...
Analytical models enable architects to carry out early-stage design space exploration several orders...
Analytical performance models yield valuable architectural insight without incurring the excessive r...
In the last decade, GPUs have emerged to be widely adopted for general-purpose applications. To capt...
Graphics Processing Units (GPUs) have been shown to be effective at achieving large speedups over co...
The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly ...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
As modern GPUs rely partly on their on-chip memories to counter the imminent off-chip memory wall, t...
In the present paper, we propose RDGC, a reuse distance-based performance analysis approach for GPU ...
Traditionally, GPUs only had programmer-managed caches. The advent of hardware-managed caches accele...
Analytical performance models yield valuable architectural insight without incurring the excessive r...
As a throughput-oriented device, Graphics Processing Unit(GPU) has already integrated with cache, wh...
Abstract—With the SIMT execution model, GPUs can hide memory latency through massive multithreading ...
The diversity of workloads drives studies to use GPU more effectively to overcome the limited memory...
Graphics processing units (GPUs) have become ubiquitous for general purpose applications due to thei...
Abstract—In a GPU, all threads within a warp execute the same instruction in lockstep. For a memory ...
Analytical models enable architects to carry out early-stage design space exploration several orders...
Analytical performance models yield valuable architectural insight without incurring the excessive r...
In the last decade, GPUs have emerged to be widely adopted for general-purpose applications. To capt...
Graphics Processing Units (GPUs) have been shown to be effective at achieving large speedups over co...
The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly ...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...