By Pallab Chatterjee
Until recently, low power engineering has been defined by the automated use of EDA tools in the design flow to help cut back on peak dynamic power. The new generation of mobile and video products has forced a change in that methodology.
There are two other fast rising architectural approaches. The first is multicore, which is prevalent in new product introductions from Nvidia, Samsung SLSI, Imagination Technology, NetlogicMicro, Broadcom, and Qualcomm. To address the usability specs required by e-readers, mobile Internet devices and other mobile information products, a new compute architecture was needed that did not just rely on “function disabling” as a power reduction technique. All of these companies introduced designs that are focused on multicore architectures, where there is complete functionality available at all times even though the process has been optimized for low power.
This low power optimization has to do with custom library design creation, modification of internal clocking schemes, datapath and buffer optimization, memory segmentation and placement, and most importantly dynamic control of the design’s power use and speed based on the data content of the information being processed on a per-packet basis. This re-architecture of products was the key enhancement with the new dual Cortex Nvidia Tegra, which is targeted to e-readers and tablet PCs, as well as the high-performance Alchemy multicore and multithreaded processors for automotive and navigation applications, and the many new video and communications appliances from Broadcom and Qualcomm.
The basis for most of these systems are ARM processors cores (A8 or A9 primarily) or MIPS cores. This shift has allowed both a performance increase in the end systems as well as a nearly doubling of the operating battery life.
The second prevalent low-power methodology is the segmentation of design to a CPU and a GPU rather than a single compute engine. While the initial impression is, this takes more power, the GPU is actually more power-efficient on graphics and some video data than the CPU, and on general use functions, the CPU is more power-efficient than the GPU. For most of the smart phones and media processing chips, this approach has replaced bigger single-processor cores with clock-gating and multi-voltage device process solutions.
These architectural changes were implemented to address both the data dependence of the power use and the yield-process variability of sub-wavelength manufacturing. As most of the applications have a very thin and small form factor, they are bound by a fixed or diminishing power envelope. To address the longer term of operation the components can lower the operating voltage, but this does not take into account the associated reduction in performance in the power envelope that is associated with it. In order to address this aspect of design, the mobile handset and mobile computing requirements have driven to the smallest geometry process flows available.
The utilization of these processes (45nm and 40nm, currently) requires restricted design rules, restricted topologies and limited device size diversity to yield well. These designs are optimized with new RTL and physical libraries, new floor plans, and power routing to highlight the data path symmetry that is required by the data sets being processed. Examples of this are new 3dmedia processor in 40nm by Samsung for mobile phones that utilize the IMG Tech 3D video and graphics engine and a high-performance ultra low power ARM CPU.
The distributed multicore approach also has been utilized in high performance for lower power products. AMD/ATI introduced the 5970 Radeon graphics card at the Consumer Electronics Show. The card has two GPUs and is a Direct X11 product with more than 4.6TFlops of peak performance. The restructuring of the device/cell library, its reliance on proven 40nm bulk CMOS processing and the use of GDDR5 memory allows the product to operate with a peak power of about 300 watts but only requires 51 watts for nominal operation. The design was optimized for power and a data control flow to support the 3200 parallel stream processors and the 160 texture units. Dynamic power is managed based on how many streams and texture units are needed at any time based on the contents of the data that being processed on any given cycle.
Most of these new systems are targeting use of Samsung’s low-power DDR3 memory, which operates at 1.3v vs. 1.5 volts and offers higher densities than DDR2. These higher-density, low power solutions can provide in excess of 35% overall power footprint reduction for the design, if used with 32nm low-power flash memories in SSD applications rather than rotating media.
The takeaway from CES this year is that architectural engineering and new firmware control methods are now seen as essential to address the functional requirements of the new mobile communication and processing platforms. This is an intelligent shift from recent years, when only feature size reduction and blind tool-based selection of power gating and power routing were in vogue.