Designing Efficient Heterogeneous Memory Architectures

The authors' model of energy, bandwidth, and latency for DRAM technologies enables exploration of memory hierarchies that combine heterogeneous memory technologies with different attributes. Analysis shows that the gap between on- and off-package DRAM technologies is narrower than that found between cache layers in traditional memory hierarchies. Thus, heterogeneous memory caches must achieve high hit rates or risk degrading both system energy and bandwidth efficiency.

MemcachedGPU: Scaling-up Scale-out Key-value Stores

This paper tackles the challenges of obtaining more efficient data center computing while maintaining low latency, low cost, programmability, and the potential for workload consolidation. We introduce GNoM, a software framework enabling energy-efficient, latency bandwidth optimized UDP network and application processing on GPUs. GNoM handles the data movement and task management to facilitate the development of high-throughput UDP network services on GPUs.

Exploiting Asymmetry in Booth-Encoded Multipliers for Reduced Energy Multiplication

Booth Encoding is a common technique utilized in the design of high-speed multipliers. These multipliers typically encode just one operand of the multiplier, and this asymmetry results in different power characteristics as each input transitions to the next value in a pipelined design. Relative to the non-encoded input, changes on the Booth-encoded input induce more signal transitions requiring ~73% more multiplier array energy.

Priority-Based Cache Allocation in Throughput Processors

GPUs employ massive multithreading and fast context switching to provide high throughput and hide memory latency. Multithreading can Increase contention for various system resources, however, that may result In suboptimal utilization of shared resources. Previous research has proposed variants of throttling thread-level parallelism to reduce cache contention and improve performance. Throttling approaches can, however, lead to under-utilizing thread contexts, on-chip interconnect, and off-chip memory bandwidth.

Scaling the Power Wall: A Path to Exascale

Modern scientific discovery is driven by an insatiable demand for computing performance. The HPC community is targeting development of supercomputers able to sustain 1 ExaFlops by the year 2020 and power consumption is the primary obstacle to achieving this goal. A combination of architectural improvements, circuit design, and manufacturing technologies must provide over a 20× improvement in energy efficiency.

High-speed Low-power On-chip Global Signaling Design Overview

On-chip global signaling in modern SoCs faces significant challenges due to wire pitch scaling and increasing die size. Conventional on-chip synchronous CMOS links have already hit a performance wall in power and latency. Although approaches based on custom low-swing equalized serial-link techniques can yield improvements, strict power/silicon budgets and non-ideal in-situ conditions of large SoCs make their design much more challenging than simply transitioning off-chip signaling technologies to onchip. Therefore, a holistic approach to the on-chip global signaling problem is required.