Composable dynamic voltage and frequency scaling and power management for dataflow applications

Composability means that the behaviour of an application, including its timing, is not affected by the absence or presence of other applications. It is required to be able to design, test, and verify applications independently. In this paper we define composable dynamic voltage and frequency scaling (DVFS) hardware, and composable power management. We ensure that the functional and temporal behaviours of an application are not affected by other applications, even when they are power managed. For dataflow applications with worst-case execution times per task, our power management is also predictable, i.e. guarantees end-to-end real-time requirements, even when the application is mapped on multiple processors that are power managed independently. Our method can be used with various DVFS architectures, such as on-chip and off-chip VF regulators. Our FPGA implementation models a system with multiple tiles, each containing a processor with local memory running a real-time operating system (RTOS) and power management. Tiles are interconnected by a network on chip, and communicate using shared memories. Experiments indicate energy savings of 68% w.r.t. no power management, and 40% w.r.t. power gating only. We also demonstrate composability and predictability on the platform in the presence of power management

Reduction operator for wide-SIMDs reconsidered

It has been shown that wide Single Instruction Multiple Data architectures (wide-SIMDs) can achieve high energy efficiency, especially in domains such as image and vision processing. In these and various other application domains, reduction is a frequently encountered operation, where multiple input elements need to be combined into a single element by an associative operation, e.g. addition or multiplication. There are many applications that require reduction such as: partial histogram merging, matrix multiplication and min/max-finding. Wide-SIMDs contain a large number of processing elements (PEs), which in general are connected by a minimal form of interconnect for scalability reasons. To efficiently support reduction operations on wide-SIMDs with such a minimal interconnect, we introduce two novel reduction algorithms which do not rely on complex communication networks or any dedicated hardware. The proposed approaches are compared with both dedicated hardware and other software solutions in terms of performance, area, and energy consumption. A practical case study demonstrates that the proposed software approach has much better generality, flexibility and no additional hardware cost. Compared to a dedicated hardware adder tree, the proposed software approach saves 6.8% area with a performance penalty of only 6.5%

Scheduling for register file energy minimization in explicit datapath architectures.

In modern processor architectures, the register file (RF) consumes considerable amount of the processor power. It is well known that by allowing software to have explicit fine-grained control over the datapath, the transport-triggered architectures (TTAs) can substantially reduce the RF traffic, thereby minimizing the RF energy. However, it is important to make sure that the gain in RF is not cancelled out by the overhead due to the fine-grained datapath control, in particular, the deterioration of code density in conventional TTAs. In this paper, we analyze the potential of minimizing RF energy in MOVE-Pro, a TTA-based processor framework. We present a flexible compiler backend, which performs energy-aware instruction scheduling to push the limit of RF energy reduction. The experimental results show that with the proposed energy-aware compiler backend, MOVE-Pro is able to significantly reduce RF energy compared to its RISC/VLIW counterparts, by up to 80%. Meanwhile the code density of MOVE-Pro remains at the same level as its RISC/VLIW counterparts, allowing the energy saving in RF to be successfully transferred to total energy saving

An energy-efficient method of supporting flexible special instructions in an embedded processor with compact ISA

In application-specific processor design, a common approach to improve performance and efficiency is to use special instructions that execute complex operation patterns. However, in a generic embedded processor with compact Instruction Set Architecture (ISA), these special instructions may lead to large overhead such as: (i) more bits are needed to encode the extra opcodes and operands, resulting in wider instructions; (ii) more Register File (RF) ports are required to provide the extra operands to the function units. Such overhead may increase energy consumption considerably. In this article, we propose to support flexible operation pair patterns in a processor with a compact 24-bit RISC-like ISA using: (i) a partially reconfigurable decoder that exploits the pattern locality to reduce opcode space requirement; (ii) a software-controlled bypass network to reduce operand encoding bit and RF port requirement. An energy-aware compiler backend is designed for the proposed architecture that performs pattern selection and bypass-aware scheduling to generate energy-efficient codes. Though the proposed design imposes extra constraints on the operation patterns, the experimental results show that for benchmark applications from different domains, the average dynamic instruction count is reduced by over 25%, which is only about 2% less than the architecture without such constraints. The proposed architecture reduces total energy by an average of 15.8% compared to the RISC baseline, while the one without constraints achieves almost no improvement due to its high overhead. When high performance is required, the proposed architecture is able to achieve a speedup of 13.8% with 13.1% energy reduction compared to the baseline by introducing multicycle SFU operations