← Back to Services

RAM

Priority Tier 4

RAM (Random Access Memory) is a fundamental component for holding programs and data actively in use, crucial for both local hardware and cloud services. AWS provides configurable RAM for virtual machines (EC2) and fully managed in-memory caching (ElastiCache) to optimize application performance. Specialized GPU memory types, GDDR and HBM, are designed for high-bandwidth graphics and high-performance computing workloads. (source_page: 4, source_page: 5)

Learning Objectives

Core Concepts of Random Access Memory (RAM)

RAM is volatile memory used for high-speed data access, supporting active programs and data for the CPU. Its specifications are crucial for system compatibility and performance.

RAM is used to hold programs and data as they are being used. Its contents are lost as soon as power is shut off or lost.
RAM upgrades are often needed during a system’s operational life to keep pace with the increasing requirements of operating systems and apps.
When specifying memory for a system, the memory module form factor, memory chip type, memory module speed, latency, error-checking features (or lack of same), and support for multi-channel memory must all be known to assure a compatible match.
SRAM (static RAM) is used for cache RAM to boost performance.
SDRAM (synchronous DRAM) was the first memory type to run in sync with the processor bus. All types of RAM in general use are based on SDRAM.
DDR uses the rising and falling edges of a clock signal and performs two transfers per clock cycle, making it faster than original SDRAM. Subsequent generations (DDR2, DDR3, DDR4, DDR5) have progressively faster transfer rates and lower power consumption.
Technical Specs: DDR SDRAM: performs two transfers per clock cycle; DDR2: transfers data twice as fast as DDR; DDR3: lower power consumption, transfers data twice as fast as DDR2; DDR4: even lower power consumption, transfer rates twice the speed of DDR3; DDR5: potential for doubled bandwidth, decreased power consumption, quadrupled DIMM capacity.
Parity checking uses nine memory bits—eight for data and one for parity checking. It can detect memory errors but it cannot fix them.
Technical Specs: 9 memory bits (8 for data, 1 for parity); detects errors, cannot fix.
ECC, error correction code RAM memory uses nine memory bits and is able to fix single-bit memory errors on-the-fly. It is common in servers. ECC can detect but not correct a double-bit error.
Technical Specs: 9 memory bits; fixes single-bit memory errors on-the-fly; detects but cannot correct double-bit errors.
Buffered (registered) memory is used in many servers and some workstations or desktops. It contains a small register that acts as a buffer between the DIMM and the memory controller. This buffer chip helps maintain stability when large amounts of RAM are installed, but it slows down the system slightly.
SO-DIMM (SODIMM) modules are used primarily in laptops as a small form factor equivalent to full-size DIMM modules. They are available in the same memory types as regular DIMMs.
Technical Specs: Available in 214-pin MicroDIMM (for DDR2 SDRAM) and 244-pin MiniDIMM (for DDR2 SDRAM) designs.
Multi-channel systems address multiple identical memory modules (same size, speed, and latency) as a logical bank for faster memory access. Single-channel systems address a single DIMM as a logical memory bank.
Technical Specs: Single-channel: addresses one DIMM; Dual-channel: addresses two modules; Triple-channel: addresses three modules; Quad-channel: addresses four modules.
The primary advantage of using quad-channel RAM is improved data transfer rates. It utilizes four memory channels simultaneously, allowing for increased bandwidth and faster data transfer between the RAM and the CPU. Quad-channel RAM does not have any effect on storage. While quad-channel RAM can offer some benefits for multitasking scenarios, it is not its primary advantage.
This distinction refers to the groups of memory chips that a memory controller accesses, not necessarily their physical location on the module. Single-sided modules have a single bank of 64-bit memory chips. Double-sided modules have two banks of 64-bit memory, which the memory controller sees separately.
Technical Specs: Single-sided: single bank of 64-bit memory chips; Double-sided: two banks of 64-bit memory chips seen separately by controller.
When installing memory modules, be sure to use ESD protection, to line up the module with the socket, and to push it into place until the locking tab or tabs swivel up into place. On some systems, it might be necessary to relocate or temporarily disconnect power or data cables or even remove the cooling fan from the CPU heatsink to gain access to memory slots.
Traditional RAM modules are often labeled with a PC-XXX designation, where the number indicates the speed of operation in MHz multiplied by the 8-byte bus width to determine the bandwidth.
Technical Specs: PC-100: 100 MHz speed, 8 byte wide bus, 800 MB/s bandwidth; PC-133: 133 MHz speed, 8 byte wide bus, 1066 MB/s bandwidth; PC-2700: 333 MHz clock speed, 8 Bytes, 2700 MB/s bandwidth; PC-3200: 400 MHz clock speed, 8 Bytes, 3200 MB/s bandwidth.
DDR memory is categorized by its bus clock (actual clock speed) and data transfer rate (Mega Transfers per second, MT/s), which is typically twice the clock speed for DDR memory due to two transfers per clock cycle.
Technical Specs: DDR2: 400 MHz to 1066 MHz (some up to 1200 MHz); DDR3: 800 MHz to 2133 MHz (some up to 2400 MHz); DDR4: 2133 MHz to 3200 MHz (some up to 4266 MHz). Example: DDR4-3200 has a bus clock of 1600 MHz and a data transfer rate of 3200 MT/s.

RAM in AWS Compute Services

AWS provides configurable memory options across its compute and caching services, allowing users to tailor resources to specific workload demands for performance and cost efficiency.

Memory is a key configurable resource in AWS, affecting the performance and cost of various services.

Amazon EC2 Instances - General Configuration

Amazon EC2 (Elastic Compute Cloud) provides virtual machines (servers) with configurable RAM, allowing users to rent and manage these resources in the cloud. EC2 instance types determine the hardware resources, including RAM, allocated to the instance. Users can also manually configure memory performance.
configurable_resource: RAM (Memory)
Use Cases:
  • General purpose workloads
  • Any application requiring specific memory allocation

Amazon EC2 Instances - Specific Examples and Types

EC2 instance types offer varying RAM allocations. 'General Purpose' instances provide a balance of compute, memory, and networking, suitable for web servers. 'Memory Optimized' instances feature large amounts of RAM for memory-intensive workloads.
t2.micro_ram: 1 GB
c1.large_ram: 7 GB
memory_optimized_purpose: Large amounts of RAM for in-memory databases, caching, and in-memory analytics/BI reporting.
Use Cases:
  • Web servers
  • Code repositories
  • In-memory databases
  • Caching
  • BI reporting

Amazon ElastiCache - In-Memory Caching

Amazon ElastiCache is a fully managed, in-memory caching service designed for ultra-fast data access. RAM is more critical than CPU when selecting node types for in-memory caches.
service_type: In-memory caching service
node_type_selection_criteria: memory requirements (RAM is more critical than CPU for in-memory caches)
Use Cases:
  • Offloading primary databases to reduce latency
  • Improving application performance
  • Externalizing user sessions
  • Real-time leaderboards
  • Messaging queues
  • User recommendations

AWS Batch - Memory Requirements

AWS Batch supports running computing jobs that can require significant CPU and memory resources.
example_memory_requirement: 520 GiB
Use Cases:
  • Hourly batch jobs needing significant CPU/memory
  • Migrating legacy applications with high resource demands

EC2 Hibernation: Preserving In-Memory State

EC2 hibernation provides a mechanism to temporarily stop an instance while preserving its in-memory state, allowing for faster restarts.

EC2 hibernation preserves the in-memory RAM state of an EC2 instance when stopped. The RAM state is written to a file on the root EBS volume, which must be encrypted. When the instance is restarted, the data is loaded back from the EBS volume to RAM.
Technical Specs: Root EBS volume must be encrypted; RAM state written to root EBS volume.
Hibernation significantly reduces startup time for applications and services by avoiding OS boot, user data scripts, and cache reloads. The application state is restored as if it was 'frozen', allowing for nearly instant resumption from its previous running state.
EC2 hibernation has specific requirements and limitations.
Technical Specs: RAM size must be less than 150 GB; not supported for bare metal instances; root volume must be EBS encrypted; available for On-Demand, Reserved, and Spot Instances; instance cannot be hibernated for more than 60 days; only supported for specific AMIs (Amazon Linux 2, Ubuntu, RHEL, CentOS, Windows).

GPU Memory Technologies

GPU memory, also known as VRAM, is specialized for time-critical workloads in graphics processing and high-performance computing, offering quick access to data for accelerated execution. There are two primary types: GDDR and HBM.

GPU memory is distinct from CPU RAM, optimized for parallel processing and high-bandwidth requirements.

Introduction to VRAM (Video Random Access Memory)

GPU memory is often referred to as VRAM. It is similar to CPU memory and traditional RAM, storing data locally for quick access and execution. Larger VRAM capacity allows more data to be stored on the GPU memory for fast short-term access, reducing the need to constantly access slower physical long-term memory.
Use Cases:
  • Rendering images, videos, and animations for display
  • Handling time-critical workloads
  • Processing data for quick access and execution

GDDR (Graphics Double Data Rate) Memory

GDDR is a type of memory specifically designed and optimized for use in graphics cards, similar to DDR but with higher speed and bandwidth. GDDR memory chips are individual components soldered to the PCB surrounding the GPU die, allowing for variable memory capacities.
latest_standard_GDDR6_per_pin_data_rate: 16Gb/s
latest_standard_GDDR6_max_memory_bus_width: 384-bits
RTX_6000_Ada_peak_memory_bandwidth: 960GB/s (near 1 TB/s)
NVIDIA_RTX_4090_memory: 24GB GDDR6X
NVIDIA_RTX_6000_Ada_memory: 48GB GDDR6 ECC
NVIDIA_RTX_4060_Ti_variants: 8GB and 16GB
Use Cases:
  • Consumer and professional GPUs
  • CAD
  • 3D Design
  • AI training (memory size dependent workloads)
  • Competitive gaming (memory speed dependent workloads)
  • 90% of mainstream applications

HBM (High Bandwidth Memory)

HBM is designed to provide a larger memory bus width than GDDR, transferring larger data packages at once. Although a single HBM chip is slower than a single GDDR6 chip, its wider bus width, smaller capacity, and stackability/scalability make it more powerful, efficient, and faster overall. HBM is built directly into the GPU die and is stacked.
latest_standard_HBM3_bus: 5120-bit
latest_standard_HBM3_bandwidth: 3.35TB/s
NVIDIA_A800_40GB_Active_GPU_HBM_configuration: 5 active stacks of 8 HBM DRAM dies (8‑Hi) each with two 512‑bit channels per die for a total width of 5120-bits.
Use Cases:
  • HPC (High-Performance Computing)
  • Highly niche workloads requiring maximum bandwidth
  • Simulation type workloads
  • AI training
  • Analytics
  • Edge computing and inferencing
  • NVIDIA DGX systems requiring fast GPU memory bandwidth speeds for NVLink interconnectivity

Comparison: GDDR6 vs. HBM Memory

comparison-table

The choice between GDDR6 and HBM memory depends on specific workload requirements, performance needs, and cost considerations, as they each offer distinct advantages.

Both GDDR and HBM have their advantages and disadvantages, catering to different performance and cost profiles.

Option Accessibility & Cost Primary Use Case Bandwidth / Bus Width (latest standards) Physical Configuration Modularity / Configurability Performance Characteristics (relative)
GDDR6 More accessible and less expensive (mainstream GPU memory type). Suitable for 90% of applications, including small to medium scale AI training, rendering, analytics, simulation, data intensive workloads. Top-end models like RTX 6000 Ada are typically not memory-bound in most use cases. Peak per-pin data rate of 16Gb/s, max memory bus width of 384-bits (GDDR6). RTX 6000 Ada peak memory bandwidth: 960GB/s. Individual chips soldered to the PCB surrounding the GPU die. Memory capacity is configurable by adding more VRAM chips or using larger capacity chips (e.g., 8GB vs 16GB RTX 4060 Ti). High bandwidth, but may limit lower-end GPUs. Higher bandwidth increases result in minor speed improvements for most applications.
HBM Less accessible, more niche, expensive. Found only in flagship accelerators and data center GPUs (e.g., H100, A800). HPC and highly niche workloads requiring the most bandwidth where speed in accessing data is imperative. Includes simulation, AI training, analytics, edge computing, and inferencing. Essential for GPU-to-GPU interconnectivity (NVLink). Larger memory bus width (e.g., HBM3 with 5120-bit bus and 3.35TB/s bandwidth). Sits inside the GPU die and is stacked (e.g., 5 active stacks of 8 HBM DRAM dies). Not configurable like GDDR; capacity is fixed per GPU die SKU (though vendors can disable stacks for stability/power). Provides significantly larger bus-widths to parallelize per-pin rate. Highly efficient. Crucial for applications where minor speed improvements are paramount and for reducing communication bottlenecks.

Exam Tips

Glossary

RAM
Random Access Memory. Used to hold programs and data as they are being used; its contents are lost when power is shut off.
SRAM
Static RAM. Used for cache RAM to boost performance.
SDRAM
Synchronous DRAM. The first memory type to run in sync with the processor bus; all types of RAM in general use are based on SDRAM.
DDR
Double Data Rate. A memory technology that performs two data transfers per clock cycle, using both rising and falling edges of a clock signal.
ECC
Error Correction Code RAM. Memory that uses nine memory bits and is able to fix single-bit memory errors on-the-fly, common in servers.
VRAM
Video Random Access Memory. GPU memory that stores data locally for quick access and execution for graphics and time-critical workloads.
GDDR
Graphics Double Data Rate. A type of memory specifically designed and optimized for use in graphics cards, typically faster than standard DDR memory with higher bandwidth.
HBM
High Bandwidth Memory. Memory designed to provide a larger memory bus width than GDDR memory, resulting in larger data packages transferred at once, often stacked and integrated into the GPU die.
SO-DIMM
Small Outline Dual Inline Memory Module (SODIMM). Memory modules primarily used in laptops as a small form factor equivalent to full-size DIMM modules.
MCC
Memory Controller Chip. Keeps track of the physical location and makeup of RAM and provides the CPU with requested bytes.

Key Takeaways

Content Sources

Introduction to Amazon ElastiCache Introduction to Amazon ElastiCache AWS Cost Optimization Deep Dive PeaceOfCode Chapter 4: RAM Extracted: 2026-01-26 14:24:10.419183 Model: gemini-2.5-flash