AI Chips 101: Understanding Latency in Computing

01

Memory, bandwidth, and latency relationship

When discussing CPU computation latency, we need to deeply understand the relationship between memory, bandwidth, and latency, as they collectively impact system performance.

✅ Relationship Between Memory and Bandwidth

The speed of memory and system bandwidth together determine the efficiency of data transfer between the CPU and memory. Higher memory bandwidth allows more data to be transferred per unit time, reducing memory access latency.

✅ Relationship Between Bandwidth and Latency

High bandwidth generally reduces data transmission time and can indirectly lower latency. However, increasing bandwidth does not always linearly decrease latency, as other factors (such as data processing complexity and transmission distance) also play a role. In low-bandwidth environments, latency increases significantly because data takes longer to reach its destination, especially when transferring large amounts of data.

✅ Relationship Between Memory and Latency

Memory speed and latency directly impact CPU access time. Low-latency memory enables faster data transfer and instruction execution, reducing CPU wait times and overall computation latency. Memory type and architecture (e.g., DDR vs. SRAM, single-channel vs. dual-channel) also affect access latency. Optimizing memory configurations can significantly reduce latency and improve system performance.

02

Factors Affecting Computation Latency

CPU Clock Frequency: Higher clock frequencies enable the CPU to process instructions faster, reducing computation latency. However, increasing clock frequency also raises power consumption and heat generation, requiring efficient cooling mechanisms.

Pipelining Technology: Pipelining divides instruction execution into multiple stages, allowing different instructions to be processed simultaneously, improving throughput and reducing latency. However, pipeline depth and efficiency directly impact latency.

Parallel Processing: Multi-core processors and hyper-threading allow multiple instructions to execute simultaneously, significantly lowering computation latency. The efficiency of parallel processing depends on the parallelizability of tasks.

Cache Hit Rate: A high cache hit rate significantly reduces memory access latency and improves overall performance. Cache misses lead to higher memory access latency.

Memory Bandwidth: Higher memory bandwidth reduces data transmission bottlenecks, lowering memory access latency and improving computational performance.

✅ Latency Analysis

• Memory Latency: Represented in the diagram by long red arrows, indicating the total time required to load data into the cache. This is a key factor affecting computation speed.
• Computation Latency: Multiplication and addition operations each have independent latencies, marked with small red arrows.
• Cache Operation Latency: The latency for reading and writing cache, which is relatively short, marked with green arrows.

✅ Latency Sources

CPU latency arises from various factors, including hardware design, memory access, and system resource contention. The diagram shows a physical distance between the CPU and DRAM. In real hardware, data must travel across this distance via the memory bus. While electrical signals travel at near-light speeds over short distances, there is still measurable delay, which is part of memory access latency.

✅ Signal Propagation Delay Calculation

Assume a computer with a clock frequency of 3 GHz, meaning each clock cycle is approximately: 1/3,000,000,000 sec≈0.333 nanoseconds1 / 3,000,000,000 \text{ sec} ≈ 0.333 \text{ nanoseconds}1/3,000,000,000 sec≈0.333 nanoseconds

The electrical signal propagation speed in conductors is about 60,000,000 meters/second. The signal transmission distance between the chip and DRAM is 50-100 mm.

• For a 50 mm distance: Propagation delay≈0.833 ns≈2.5 clock cycles\text{Propagation delay} ≈ 0.833 \text{ ns} ≈ 2.5 \text{ clock cycles}Propagation delay≈0.833 ns≈2.5 clock cycles
• For a 100 mm distance: Propagation delay≈1.667 ns≈5 clock cycles\text{Propagation delay} ≈ 1.667 \text{ ns} ≈ 5 \text{ clock cycles}Propagation delay≈1.667 ns≈5 clock cycles

These propagation delays contribute to CPU clock cycles and overall computation latency.

03

Factors Affecting Computation Speed

Computation speed depends on multiple factors, including memory latency, cache hit rate, computational efficiency, and data write-back speed. According to the diagram, the decisive factor is memory latency, which refers to the inherent delay in retrieving data from DRAM into the cache. Since DRAM is much slower than the cache and CPU registers, this process is often the most time-consuming.

✅ Impact of Memory Latency

The diagram highlights the significant effect of memory latency, with load operations (Load from DRAM) taking up a considerable amount of time. During load x[0] and load y[0], the CPU must wait for data retrieval from main memory before proceeding with calculations.

✅ Blocking of Computation Process

High memory latency significantly delays the entire computation process. Even though subsequent calculations (multiplication, addition) and cache operations (reading/writing) are relatively fast, the excessive memory latency slows down overall execution. While waiting for data loading, CPU resources remain idle, reducing computational efficiency.

04

Summary and Insights

CPU computation latency refers to the time from issuing an instruction to completing execution. It consists of instruction fetching, decoding, execution, memory access, and write-back stages. Optimizing computation performance and designing efficient computing systems require reducing latency.

Key takeaways:

• Memory speed, bandwidth, and latency directly affect CPU access time. Optimizing memory configurations (e.g., increasing cache size, improving memory bandwidth) can significantly reduce latency and enhance system performance.
• Methods to reduce CPU computation latency include:
  • Increasing clock frequency
  • Optimizing pipeline design
  • Expanding cache size
  • Using efficient parallel algorithms
  • Enhancing memory subsystem performance

These measures help improve overall computing performance.

Related:

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2. Long-Term Data Storage: Best Options Compared | DiskMFR
3. RAM Speed vs CPU Power: Maximizing Performance
4. Processing in Memory: Key to Next-Gen Storage Innovation
5. Boost Ryzen 9000: How AGESA 1.2.0.2 Improves Performance

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