The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
The reliable way to measure GPU utilization is to combine fleet telemetry with application traces. Use NVIDIA Data Center GPU Manager (DCGM) and DCGM Exporter to establish continuous, comparable measurements across devices or GPU instances. Then use Nsight Systems or Nsight Compute to explain which CPU activity, synchronization point, memory transfer, kernel, or instruction produced the pattern. A single “GPU utilization” percentage cannot distinguish useful computation from a warp waiting on memory, a brief copy operation, or an idle gap between launches.
This workflow answers both practical questions: “How do I measure GPU utilization?” and “How do I find bottlenecks in enterprise AI infrastructure?” It starts with a representative workload window, validates what each metric means, correlates telemetry with throughput, and escalates only when the fleet data shows that application-level attribution is necessary.
What GPU utilization actually measures
GPU utilization is not one universal statistic. DCGM exposes separate interval-based signals for engines, streaming multiprocessors (SMs), tensor pipelines, device memory, occupancy, PCIe, and NVLink. Each describes a different kind of activity, and each is averaged over a measurement interval. The correct interpretation depends on the field definition, the entity being measured, and the workload phase.
For example, DCGM defines SM activity as the fraction of time that at least one warp was active on an SM, averaged across the SMs. A warp waiting for a memory request still counts as active. Therefore, a high SM-activity value does not prove that arithmetic instructions are progressing efficiently. NVIDIA’s DCGM profiling guidance states: “A high value in one field does not alone prove that the application is compute- or memory-bound; compare several related metrics over a representative interval and correlate them with application throughput.”
#1 Best Overall
- Valued Carpenter Pencil Set: You will get 2 pcs solid carpenter pencils with 26 piece 2.8 mm refills, 1 replaceable sharpener, 1 plastic storage box.The complete carpenter pencils combination allows you to finish your work faster and more easily
- Deep Hole Marker Pencil: The deep-hole construction pencils adopts 45mm elongated tip design, which is more convenient to mark in the small hole or in other tight areas that other carpenter markers cannot reach
- Carpenter Pencils with Sharpener: The sharpener is screwed into the top of the work pencil, which won't get lost either. Built-in pencil sharpener that keep the lead with pointed and smooth to Improves line of sight in fine work
- Stronger Solid Lead: This work pencil is matched with a 2.8 mm thick lead , which is much thicker and stronger during the drawing process of construction work, it will not break or damage easily
- Marks on Various Surfaces: 3 colors solid construction pencil can marks on various surfaces,such as metal, plastic, wood, paper etc. Ideals for woodworkers, contractors, craftsmen, builders, merchants and masons
Nsight Systems uses a different concept in its low-utilization analysis. Its utilization is based on time in API traces, not the share of GPU resources consumed. As NVIDIA explains, “The utilization refers to the ‘time’ utilization and not the ‘resource’ utilization.” A small memcpy can therefore count as GPU-in-use for the duration of the operation just as a large kernel does, and overlapping operations can make a time-utilization segment exceed 100 percent.
Build a measurement plan before collecting data
Choose a representative workload window
Select a steady-state training or inference phase rather than startup, model loading, checkpointing, or shutdown. Record application throughput during the same interval: examples per second, tokens per second, requests per second, latency percentiles, or another business-relevant measure. Keep the model, batch size, precision, replica count, and input mix fixed while comparing runs.
Compare equivalent phases across replicas and devices. A short warm-up interval, an evaluation pass, and a gradient-communication phase can have very different legitimate profiles. Label the phase, host, GPU or GPU instance, process, and software configuration with every observation so that a later comparison does not mix unlike work.
Recommended Free Tools
Define the question the metric must answer
- Is a device receiving work continuously? Examine engine and SM activity over time and look for sustained gaps.
- Is the measured phase using tensor pipelines? Compare tensor-pipe activity with SM activity and throughput.
- Is device memory traffic prominent? Compare DRAM activity with occupancy, tensor activity, and achieved throughput.
- Are replicas or GPU instances behaving differently? Compare the same fields, entities, labels, and workload phase side by side.
- Is the cause inside the application? Move from DCGM interval telemetry to an Nsight trace or compute profile when the fleet data cannot attribute a kernel or host-side delay.
Establish fleet visibility with DCGM
DCGM provides tools and libraries for observing and managing NVIDIA data-center accelerators. It is the appropriate first layer for continuous visibility because it can show whether devices are busy, underused, or imbalanced without instrumenting every application.
Deploy DCGM Exporter
DCGM Exporter selects configured DCGM fields and exposes them in Prometheus format at a /metrics endpoint. NVIDIA documents three common deployment paths:
Rank #2
- Ergonomically Designed: Work in tight areas with a compact design that gets into tough spots
- Both tools are designed to fit into difficult to reach spaces
- Complete a wide range of applications with a high-performance motor that delivers up to 300 UWO, and an impact driver delivering up to 1,400 in-lbs of torque
- Both the DEWALT impact driver and drill driver feature integrated LED work lights with a convenient 20-second delay, ensuring enhanced visibility in dimly lit or challenging work areas
- One-Handed Loading - Keep one hand free with a 1/4 in. hex chuck that accepts 1 in. bit tips
- A package-managed service on the host.
- A container deployment.
- A Kubernetes DaemonSet that runs an exporter on each eligible node.
Choose the path that matches the operating model of the cluster. In Kubernetes, ensure the DaemonSet reaches every node that should be monitored and that the Prometheus collector can discover and scrape each exporter. In a host or container deployment, verify network reachability, service credentials, and the exporter’s runtime configuration.
Treat configuration as a request, not proof
An entry in an exporter configuration does not guarantee that a time series will be emitted. A row can be skipped when the GPU, DCGM field, driver, entity type, permissions, or deployment does not support it. Hardware partitioning and GPU instances can also change which entities are visible.
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Inspect the actual exporter endpoint and record which fields and labels are present. Confirm that the exporter and DCGM versions are a supported pair for the release in use. Check the endpoint after upgrades, driver changes, node replacement, or a change in GPU-instance configuration; a previously available field can disappear when support conditions change.
Validate the monitoring path
- Identify every monitored node and the GPU or GPU-instance entities visible on that node.
- Open the exporter’s
/metricsendpoint and confirm that expected fields are present with current timestamps or changing values. - Check labels for device identity, GPU instance, workload or process scope where supported. Do not assume that a label exists merely because the hardware supports that concept.
- Compare a known active workload with an idle period to verify that the selected fields respond in a plausible direction.
- Record missing fields and the corresponding hardware, driver, DCGM, exporter, permission, and deployment details before escalating.
Interpret the measurements together
The following signals are useful when read as a group. Their exact availability depends on the hardware, driver, DCGM version, entity, permissions, and exporter configuration.
| Signal | What it represents | What it cannot prove alone |
|---|---|---|
| SM activity | Fraction of time at least one warp was active on an SM, averaged across multiprocessors. | That warps were performing useful arithmetic; memory-waiting warps still count as active. |
| Tensor activity | Fraction of cycles during which the tensor pipe was active, averaged over an interval. | Why tensor use is low, or that a low value is wrong for the measured workload phase. |
| DRAM activity | Fraction of cycles in which device-memory traffic was present. | That the workload is memory-bound; traffic may coexist with unused compute capacity. |
| SM occupancy | Resident warps as a fraction of the maximum supported resident warps. | Higher effective performance; occupancy alone does not guarantee efficient execution. |
| Graphics/compute engine activity | Broad activity of the relevant device engine. | Which kernel, instruction, or host action caused the activity. |
| PCIe and NVLink traffic | Data movement over the corresponding interconnect. | Whether movement is the limiting factor without a throughput and timing comparison. |
Use the same interval for all related fields and for application throughput. A high DRAM value with poor throughput is a reason to inspect more signals, not a verdict. Likewise, high SM activity with disappointing throughput warrants a comparison of tensor activity, memory activity, occupancy, and trace evidence.
Rank #3
- 【Great Compatibility】This Katerk 1/4 inch hex shank bit holder is specifically designed for 1/4 inch hex shank drill bits. It's compatible with most 1/4 fast hex handles, hex sockets, various electric screwdrivers, and handheld screwdrivers. The bit holder makes it a valuable addition for any handyman.
- 【Secure and Safe】Built with a secure backup nut design, each drill bit holder securely locks onto your bits, ensuring they stay firmly in place. Additionally, our bit holder incorporates a high-quality steel ball rolling design that holds up to several kilograms of weight, ensuring your various drill bits don't fall off.
- 【Easy One-Handed Operation】The bit holder for impact driver allows you to change bits single-handedly, simplifying your workflow. Its multi-color design further allows for quick identification of the drill bit you need.
- 【Compact and Convenient】Thanks to its compact size, this 1/4 inch bit holder is easy to carry around. The bit holder allows for easy attachment to various tools, making this a convenient addition to your construction accessories. The Katerk bit holder is cast from high-quality alloy material, promising a long product lifespan. Despite its rugged strength, the bit holder remains lightweight, making it portable.
- 【Cool Christmas Gift For Men Stocking Stuffers】 This screwdriver bit holder, driver bit holder, impact bit holder, can be given as a gift to your loved one, especially for anyone involved in construction or electrical work. It's a must-have for stocking stuffers for men and women, tools gifts for dad, tech gadgets for men, gifts for dad, gifts for him, gifts for husband, gifts for boyfriend, cool gadgets for men, and cool gifts for dad.
Use time-series shape to identify symptoms
Plot values over time instead of reducing a run to one average. Sustained low activity, repeated gaps, bursts that align with input preparation, and uneven values across replicas are useful clues. They do not, by themselves, identify the responsible subsystem.
| Observed pattern | What it can indicate | Next check |
|---|---|---|
| Long GPU activity gaps | Work may not be reaching the GPU continuously. | Inspect an Nsight Systems trace alongside CPU samples, blocked-state backtraces, synchronization APIs, and NVTX ranges. |
| High SM activity but disappointing throughput | Active warps may be waiting on memory rather than computing efficiently. | Compare tensor activity, DRAM activity, occupancy, and throughput, then profile the application. |
| Low tensor activity in an AI phase | Tensor-pipe use may be limited in that particular phase. | Verify the phase and compare SM, memory, and throughput signals before attributing a cause. |
| High device-memory activity | Device-memory traffic is present. | Compare related metrics and throughput over the same representative interval. |
| Inconsistent devices or GPU instances | Entities, workload phases, or supported fields may differ. | Check entity selection, MIG visibility, field support, labels, permissions, and actual exporter output. |
| Profiling fields become blank during an Nsight session | DCGM profiling collection may be paused or competing for counter access. | Check profiling watches and coordinate pause/resume across host-engine clients. |
Find idle gaps with Nsight Systems
When DCGM shows underuse but not the reason, collect an Nsight Systems trace for the same representative phase. Its timeline can associate GPU operations with CPU launches, API calls, synchronization, copies, and application ranges.
Understand the low-utilization rule
Nsight Systems’ low-utilization findings are based on time occupied by GPU operations in API traces. They do not report how many SMs, tensor units, or memory channels those operations consumed. A single short copy and a large, fully occupying kernel are both “in use” while they run. Concurrent operations can also make a time-based segment exceed 100 percent.
The documented GPU Starvation rule marks idle periods longer than 500 milliseconds. That threshold is adjustable and belongs to the tool’s analysis rule; it is not an industry-wide definition of GPU starvation or a universal performance target.
Investigate what happens during the gap
- Use CPU sampling to see whether launch threads are busy, preempted, or spending time in runtime or framework code.
- Inspect operating-system runtime blocked-state backtraces for waits on locks, I/O, scheduling, or other host resources.
- Review synchronization-related operating-system runtime APIs to locate waits that prevent launches or overlap.
- Add or inspect NVTX annotations so model stages, input pipelines, communication phases, and batches are visible in the timeline.
- Compare the trace’s gap boundaries with DCGM time series and application throughput to ensure the same phase is being explained.
Escalate to Nsight Compute for kernel-level attribution
Nsight Compute is appropriate when the question has become kernel-specific: which kernel is slow, which instruction mix is limiting progress, or whether a kernel’s memory behavior and occupancy explain the throughput. DCGM profiling metrics are interval averages, not kernel traces, so they cannot identify the source line or instruction responsible for a fleet-level reading.
Rank #4
- Long Nib and Deep Hole Marker: Our mechanical carpenter pencil with 45mm nib is designed for easy marking of deep holes or narrow areas. These construction pencils are the great choice for woodworking tools, construction tools, carpenter tools, contractor tools, wood carpentry tools and architect tools
- Extra Refills in 2 Colors for Versatile Marking: The construction mechanical pencil comes with 12 extra 2.8mm refills, including 6 red and 6 black refills. The black refill is suitable for light surfaces, while the red wax is perfect for dark surfaces. Our carpenter mechanical pencil makes sure that you'll have an ample supply for extended use
- Built-in Sharpener: Our construction pencil comes with a built-in sharpener to ensure the mechanical pencil tip is always sharp and ready for use. Never buy an extra pencil sharpener again. A great tool for any woodworker pencil, contractor pencils. The refill can easily be extended or retracted with a simple click of the pencils mechanical, allowing you to work more efficiently and accurately
- Portable Clip Design: Our deep hole construction pencil features a portable clip design, easy to carry and attach to your pocket or tool box, so that you can keep the carpenter pencils mechanical close at hand, making it a convenient tool to have on the go. Great gifts choice for carpenters
- Stronger Pencil Lead: The black refills are made of lead, sturdy and smooth. The red refills are made of wax, clear and light. These marking pencils are much thicker and stronger than normal pencils during the marking process of construction work, suitable for various surfaces, such as glasses, metal, boards, floors, walls, furniture, etc. The written marks can be easily wiped with a wet paper towel when needed
Use the narrowest trace or profile that answers the question. Start with a short, reproducible phase and one representative process or device when possible. Preserve the workload configuration and record whether the profile includes warm-up, communication, evaluation, or steady-state work.
Prevent counter conflicts during profiling
DCGM profiling metrics and NVIDIA developer profilers can contend for the same hardware counters. Before starting an Nsight Systems or Nsight Compute session, pause DCGM profiling collection as documented by NVIDIA. Resume collection after the profile finishes.
The pause applies to the whole host engine, not only to the client that requested it. Profiling fields return blank values while collection is paused. Coordinate with other monitoring users so that a diagnostic interval is not mistaken for a device outage or silently removed from fleet dashboards. Mark the pause and resume times in the incident record.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose the right tool for each question
| Need | DCGM and DCGM Exporter | Nsight Systems | Nsight Compute |
|---|---|---|---|
| Continuous fleet visibility | Primary choice; interval metrics can be scraped and stored in Prometheus-compatible systems. | Not designed as the fleet telemetry layer. | Not designed as continuous fleet telemetry. |
| Compare devices, replicas, or GPU instances | Effective when entities, labels, and fields are supported and validated. | Usually a targeted trace of selected workloads. | Usually a targeted kernel profile. |
| Explain idle gaps | Shows the symptom through time-series activity. | Shows CPU/API, synchronization, copies, and GPU timeline relationships. | Not the first tool for host-side gaps. |
| Identify a kernel or instruction cause | Cannot attribute to a source line or individual instruction. | Can associate operations and launches with timeline context. | Provides kernel-level execution and instruction analysis. |
| Operational compatibility | Requires supported fields, versions, permissions, and counter availability. | May require pausing DCGM profiling collection. | May require pausing DCGM profiling collection. |
A practical escalation runbook
- Write down the workload contract. Record model, batch or request configuration, precision, replica count, phase, throughput target, and comparison baseline.
- Verify telemetry support. Confirm the exporter endpoint, field definitions, entity visibility, labels, permissions, hardware, driver, and compatible DCGM/exporter versions.
- Capture a steady-state interval. Store related DCGM fields and application throughput together, with synchronized timestamps.
- Compare like with like. Check replicas, devices, GPU instances, and workload phases without mixing unlike entities.
- Classify the symptom. Decide whether the evidence is primarily idle time, high activity with low throughput, memory traffic, low tensor use, or cross-device imbalance.
- Trace the relevant interval. Use Nsight Systems for launch gaps, host waits, synchronization, and data movement. Add CPU sampling, blocked-state analysis, and NVTX ranges.
- Profile a representative kernel. Use Nsight Compute when the trace points to a kernel-level question. Pause DCGM profiling first and document the pause window.
- Document the evidence chain. Preserve the workload phase, metric definitions, entity labels, trace times, tool versions, and the throughput change that justifies remediation.
Troubleshoot missing or misleading data
A configured field is absent
Check whether the selected GPU or GPU instance supports the field, whether the driver and DCGM release expose it, whether the exporter is using a compatible version, and whether permissions allow access. Confirm the entity type and inspect the live /metrics output rather than relying on configuration alone.
Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteOne replica appears idle
First verify that the replicas are doing the same phase and that labels identify the intended device or GPU instance. Then check process or workload visibility, MIG entity selection, exporter coverage on the node, and whether the replica is waiting on host work or synchronization. A single aggregate average can hide this imbalance.
Best Value
- Milwaukee Ink all Fine Point Marker, Black, 4 Per Pack
- 4 per pack Features Clog Resistant Marker Tip Writes through Dusty, Wet and Oily Surfaces Durable Marker Tip for Writing on Concrete, OSB and Rough Surfaces
- Clog resistant tip writes on dusty, wet and oily surfaces and is optimized for rough surfaces such as OSB, cinderblock and concrete
- Hard hat clip- attaches for easy access
- Quick dry time with reduced smearing and marking
Utilization looks high but the service is slow
Do not conclude that the GPU is healthy or that it is compute-bound from SM activity alone. Compare tensor activity, DRAM activity, occupancy, interconnect traffic, and application throughput. A trace can reveal memory waits, short operations separated by gaps, synchronization, or host-side launch delays.
Values disappear while profiling
Check whether DCGM profiling watches were paused for Nsight, whether another host-engine client changed the watch state, and whether the profile has ended. Restore collection and verify that fields reappear before treating blank values as hardware or exporter failure.
What a defensible bottleneck claim looks like
A defensible claim names the workload phase, entity, measurement definitions, time window, and throughput consequence. For example: an inference phase on a specified GPU instance showed repeated API-trace idle gaps longer than the configured Nsight Systems threshold; CPU blocked-state and synchronization evidence overlapped those gaps; and throughput fell relative to a matched replica. That is materially stronger than saying “GPU utilization was 40 percent.”
Keep the conclusion proportional to the evidence. Fleet telemetry can establish that a device is underused or that replicas differ. Nsight Systems can connect gaps to host and API behavior. Nsight Compute can attribute a kernel’s execution characteristics. None of these layers should be used to claim a broader industry benchmark from a tool threshold or a single example measurement.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
