Dynamic Power Redistribution in Cluster Nodes
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Solution Overview
Problem
In power-constrained environments, existing parallel computing systems inefficiently manage power distribution among nodes during communication and computation phases, leading to suboptimal performance due to uneven power allocation and unnecessary energy waste.
Innovation Solution
A multi-node cluster with a cluster agent and node agents that dynamically reassess and redistribute power by power-gating nodes that have completed their tasks early, reallocating this power to nodes on critical paths to enhance computation speed and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If nodes continue polling the network interface card during communication wait phases to ensure message reception, then communication reliability is maintained, but CPU power consumption increases unnecessarily
Solution Approach 1:
The system dynamically adjusts CPU operational states based on workload phase. During communication wait phases, CPUs transition from active polling to idle or powered-off states, then reactivate when computation phases begin. This dynamic state adjustment resolves the contradiction by maintaining reliability during critical phases while reducing power consumption during non-critical wait phases.
Solution Approach 2:
The system uses completion packets and synchronization mechanisms to automatically trigger CPU reactivation. When a node receives a completion packet indicating other nodes have finished computation, it automatically wakes up its CPU without requiring continuous polling, thus maintaining communication reliability while minimizing unnecessary power consumption.
2Ease of operation
If power is distributed equally to all nodes to ensure fair resource allocation, then resource fairness is maintained, but nodes on critical paths cannot receive additional power to speed up overall execution
Solution Approach 1:
The power distribution system transitions from static equal allocation to dynamic adaptive allocation. Cluster agents continuously monitor node workload status and dynamically adjust power distribution in real-time, allocating additional power to nodes on critical paths during computation phases while maintaining fairness during other phases. This resolves the contradiction by making power allocation adaptive to actual system needs.
Solution Approach 2:
The system applies different power allocation strategies to different nodes based on their specific workload characteristics. Nodes identified as being on critical paths receive enhanced power allocation, while non-critical nodes receive standard allocation. This localized quality adjustment resolves the contradiction by optimizing for overall productivity without completely sacrificing fairness.
3Loss of energy
If nodes are power-gated during communication wait phases to reduce power consumption, then power efficiency is improved, but nodes experience increased latency when waking up to receive messages
Solution Approach 1:
The system performs preliminary actions by having nodes enter idle states with minimal power consumption rather than fully powering off during short wait phases. This preliminary preparation allows for faster reactivation compared to full power-gating, thus reducing wake-up latency while still achieving power efficiency improvements.
Solution Approach 2:
The system changes the power state parameter from fully powered-on to a low-power idle state during communication wait phases, rather than complete power-gating. This parameter adjustment achieves significant power efficiency improvements while maintaining sufficiently low wake-up latency for most communication scenarios.
4Reliability
If CPUs stay active during barrier synchronization to poll for messages, then message reception is ensured, but computation power is wasted during synchronization events
Solution Approach 1:
The system extracts the message reception function from the main CPU during barrier synchronization events, delegating it to the network interface card or dedicated communication hardware. This allows the CPU to enter low-power states during synchronization while ensuring messages are still reliably received by the extraction component, thus resolving the contradiction between reliability and energy efficiency.
Solution Approach 2:
The network interface card acts as an intermediary between the external network and the CPU during barrier synchronization. It receives and buffers incoming messages, then notifies the CPU only when computation phases begin, eliminating the need for continuous CPU polling while maintaining message reception reliability.
Data Source
AI summary
Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agent may be configured to reassign the unused power to the active nodes to expedite workload processing.