论文标题
使用静态数据压缩的GPU寄存器文件
A GPU Register File using Static Data Compression
论文作者
论文摘要
GPU依靠大型寄存器文件来解锁高吞吐量线程级并行。不幸的是，大型寄存器文件是饥饿的，因此寻找改善其利用率的新方法很重要。 本文介绍了一个新的注册文件组织，以有效地寄存了狭窄整数和浮点操作数，旨在利用静态分析的进步。我们表明，硬件/软件共同设计的寄存器文件组织的绩效提高高达79％，平均为18.6％，以适度的输出质量降级。
GPUs rely on large register files to unlock thread-level parallelism for high throughput. Unfortunately, large register files are power hungry, making it important to seek for new approaches to improve their utilization. This paper introduces a new register file organization for efficient register-packing of narrow integer and floating-point operands designed to leverage on advances in static analysis. We show that the hardware/software co-designed register file organization yields a performance improvement of up to 79%, and 18.6%, on average, at a modest output-quality degradation.
