GPU Inference and Training Optimization
Slash your AI/ML infrastructure costs by 30–70% while boosting inference speed and training throughput with our expert GPU optimization—covering quantization, kernel fusion, right-sizing, and continuous monitoring across A100, H100, L40S, and other GPU families.
Comprehensive GPU Infrastructure Audit
Identify inefficiencies across your entire GPU stack—cloud instances, on-prem hardware, containers, models, and pipelines. We pinpoint bottlenecks in compute, memory, networking, and execution.
- GPU utilization & idle time analysis
- Memory bandwidth & bottleneck detection
- Multi-GPU & cluster efficiency profiling
Model Optimization & Quantization
Dramatically reduce model size and inference latency with advanced quantization techniques—INT8, INT4, mixed-precision—while maintaining accuracy. Faster serving, lower memory, smaller bills.
- Post-training & quantization-aware training
- Mixed-precision (FP16, BF16, INT8, INT4)
- Model pruning & distillation
Inference & Training Acceleration
Slash inference time and training cycles with kernel fusion, compiler optimizations, and efficient serving frameworks. Deploy vLLM, TensorRT, and custom kernels for maximum throughput.
- vLLM, TGI, TensorRT-LLM deployment
- Kernel fusion & custom CUDA kernels
- Flash Attention & PagedAttention
GPU Instance Right-Sizing
Match GPU hardware to workload requirements. We analyze A100, H100, L40S, RTX, MI300, and other architectures to recommend optimal instance families—balancing performance and cost.
- Instance family selection (A100, H100, L40S, etc.)
- Spot/preemptible GPU strategies
- Multi-cloud GPU cost comparison
Container & Pipeline Optimization
Streamline ML pipelines and containerized workloads for GPU efficiency. We optimize Docker images, Kubernetes scheduling, batch processing, and caching to maximize GPU utilization.
- Docker image optimization & layer caching
- Kubernetes GPU scheduling & node pools
- Batch inference & request batching
Monitoring & Continuous Optimization
Sustain 30–70% cost savings as workloads evolve. We provide real-time GPU metrics, performance dashboards, and proactive optimization recommendations to maintain peak efficiency.
- Real-time GPU utilization dashboards
- Cost per inference/training job tracking
- Automated performance regression detection