GPU

As explained in Latency

A GPU is a processor designed with many parallel execution resources for graphics and general-purpose data-parallel computation.

A GPU is a processor with many parallel execution resources, capable of running tens of thousands of hardware threads simultaneously. This makes GPUs well suited to data-parallel workloads that apply similar calculations across different datasets. section 9.1

Unlike concurrency on one CPU core, which interleaves tasks to create an illusion of simultaneous progress, GPU execution provides true parallelism across separate execution units. section 9.1

Figure 9.1 Concurrency versus parallelism. Concurrent execution (on the left) interleaves thread execution on a single core, which provides an illusion of work happening at the same time because all threads make some progress quickly. In contrast, parallel execution (on the right) executes the threads simultaneously on different cores, providing true parallel execution.

Compare interleaved execution on one core with simultaneous execution across separate cores or execution units. section 9.1

How Latency covers it

How deep it goes

Defines GPU parallel execution and contrasts it with concurrency, but stops short of implementation details or performance measurement.

Examples

Uses interleaved single-core threads, multicore execution, and tens of thousands of GPU hardware threads as comparison examples.

What it assumes

Distinguishes concurrency from true parallelism while introducing GPU execution through CPU and multicore comparisons.

What you can do after

Evaluate whether a workload fits GPU execution by identifying repeated calculations across independent datasets.

How it connects

Connects GPUs to concurrency, parallelism, CPU cores, hyperthreading, hardware threads, and data parallelism.

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Related concepts

• batch sizeused by · Batch size is the number of items grouped together for processing or computation as a single batch.
• GPU kernelused by · A GPU kernel is an executable program or function that performs computation on a graphics processing unit, commonly using parallel threads.
• threaduses · A thread is an independently schedulable sequence or context of execution within a program or process.
• CPUcontrasts with · A central processing unit (CPU) is a general-purpose processor that executes computer instructions and performs computational operations.

This explainer was generated by Manning's knowledge graph from the text of Latency. The section links point to the parts of the book it draws on.