BRAINS · Masterclass

Accelerators and Inference

Choose the model path and chip for the workload—not the logo.

Compare managed APIs, CPU, GPU, TPU, NPU, and inference ASIC paths through quality, memory, latency, throughput, availability, and cost.

You will build

One fixed task evaluated across a managed API, CPU or local path, and scalable accelerator inference through Alternate Clouds.

Your proof artifact

Decision matrix, reproducible benchmark, failed or unsupported path, recommendation, and fallback.

Required Alternate Clouds deployment

Accelerator Bake-Off

Class requirement: create or sign in to your Alternate Clouds account, deploy the Accelerator Bake-Off template, and submit its live URL before the class is marked complete.

Create your Alternate Clouds account ↗

Use only work you own or are authorized to use.

Every submission needs a source-and-license manifest covering text, code, images, audio, video, fonts, datasets, models, weights, and AI reference inputs. Attribution alone is not permission. Questionable material stays private or is replaced before deployment or showcase.

Ask about rights clearance

01Inference path before hardware

Start with the exact model, license, quantization, context, batch, and concurrency requirement.

Applied exercise

Write a workload card before selecting a provider or chip.

02Chip families

Understand CUDA, ROCm, Metal/Core ML, TPU/XLA, Neuron, Gaudi, NPUs, and ASIC trade-offs.

Applied exercise

Screen at least three chip/runtime families against the workload card.

03The numbers that matter

Separate capacity from bandwidth, prefill from decode, and average latency from tail latency.

Applied exercise

Measure time to first token, total task time, throughput, memory, retries, and quality.

04Operability

Account for drivers, containers, cold starts, partitioning, duty cycle, capacity, and portability.

Applied exercise

Document an exit path if the preferred accelerator becomes unavailable.

The complete course adds the teaching deck, Alternate Clouds lab, source-bounded guide, review rubric, and instructor feedback.

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