A COMPARATIVE ANALYSIS OF DDR4 AND DDR5 MEMORY ARCHITECTURE
Keywords:
Computer Architecture, DDR5 SDRAM, Dual Sub-channel, Burst Length, Thermal Management.Abstract
The development of modern software demands high data transfer rates from the main memory. However, increasing conventional RAM speed is often hindered by thermal law limitations, triggering circuit temperature spikes due to forced clock speeds. This study aims to analyze DDR5 memory data bus path structural modifications in overcoming these semiconductor circuit physical limitations. The method employed is a literature study with a qualitative-descriptive approach, utilizing secondary data from Google Scholar, Garuda, and technical specification documents. The study scope is strictly confined to internal micro-architectural modifications, excluding memory capacity and density scaling parameters. Results indicate that increased data transfer rates in the DDR5 generation are achieved by restructuring the single 64-bit data bus path into a dual 32-bit sub-channel system. This modification combines with doubling the Burst Length value to BL16 to transmit large data packets simultaneously without frequent processor interruptions. In conclusion, this internal architectural engineering provides an effective solution to accelerate data transmission and maintain temperature stability without forcing memory physical frequency limits. Theoretically, these findings shift the memory optimization paradigm from frequency scaling to structural path efficiency, foundational for future scalable hardware designs.
References
H. Hanif and B. Sugiantoro, “Literature Review: Evolusi Arsitektur Komputer dalam Konteks Sistem Organisasi Komputer,” J. Media Inform., vol. 6, no. 4, pp. 2452–2457, 2025.
M. Sahyudi, “Implementation of Cache Memory Technology in Improving the Performance of Modern Computing Systems,” vol. 11, no. 6, pp. 10–17, 2025, doi: 10.29303/jppipa.v11i6.11545.
R. F. Humainah et al., “Pengaruh Kapasitas Memori RAM ( Random Access Memory ) Terhadap Kecepatan Memori Pada Laptop Universitas Sultan Ageng Tirtayasa,” vol. 1, no. 4, 2023.
C. Plates et al., “CPU Overclocking : A Performance Assessment of,” IEEE Trans. Components, Packag. Manuf. Technol., vol. 11, no. 10, pp. 1703–1715, 2021, doi: 10.1109/TCPMT.2021.3106026.
Y. Kim, “A Statistical Approach for Signal and Power Integrity Co-Design in High-Speed Interconnects Considering Non-Linear Power / Ground Noise and Bit-Patterns,” 2023.
M. Z. R. P. Y. R. A. J. M. A. A. R. Maulana, “ANALISIS STRUKTUR MEMORI : HIERARKI MEMORI PADA ORGANISASI ARSITEKTUR KOMPUTER,” Kohesi J. Sains dan Teknol., no. Vol. 3 No. 6 (2024): Kohesi: Jurnal Sains dan Teknologi, pp. 11–21, 2024.
C. Ke, “Single 32-bit Sub-Channel DDR5 DIMMs : Architecture , Performance Bounds , and Standardisation,” 2026.
R. Awal, F. Ibrahim, M. Fahmi, and A. F. Pukeng, “Evaluasi Kinerja Virtualbox Pada Laptop Berbasis Intel N100 Dengan Media Penyimpanan EMMC,” vol. 7, no. 3, pp. 423–436, 2025.
Intel, “How to Overclock Your CPU from BIOS.”
Corsair, “RAM: Tips on safely overclocking memory.”
S. Z. Z. Mufti Prasetiyo Annisa; Ahsanul Fazri, Naufal; Harefa, Arojasa, “Manajemen Penyimpanan Sementara (RAM) Dan Pengelolaannya,” Bul. Ilm. Ilmu Komput. dan Multimed., no. Vol 2 No 1 (2024): Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA), pp. 145–149, 2024.
H. Maulana, “Desain dan Analisis Kinerja Arsitektur Pendingin Cerdas untuk Mengurangi Panas Berlebih dan Korsleting pada Motherboard Laptop,” J. Inf. Syst. Technol., vol. 1, no. 2, pp. 71–79, 2025.
Kingston, “Cara Memilih RAM Terbaik untuk Overclocking.”
M. Raihan, M. N. Farras, and B. Paramita, “Studi Eksperimental Konsumsi RAM Selama Transfer Data Cloud Menggunakan Google Drive,” vol. d, no. 2, pp. 52–63, 2026.
N. Said et al., “PENGEMBANGAN APLIKASI RAM CLEANER BERBASIS C ++ UNTUK OPTIMASI PENGGUNAAN MEMORI SISTEM OPERASI,” vol. 10, no. April, pp. 53–62, 2026.
M. Arif, I. Rafif, M. Rafly, S. Bashrah, and T. Al Habib, “Evolusi Arsitektur Komputasi dan Protokol Internet Awal : Analisis Historis Teknis Generasi Pertama,” vol. 1, no. 2, pp. 38–44, 2026.
Y. Adrian, R. C. Lesmana, and S. Sudimanto, “Analisis Performa pada Video Graphic Array (VGA) Nvidia GTX 950M DDR3 dan Nvidia GTX 950M GDDR5,” Media Inform., vol. 20, no. 2, pp. 91–96, 2021.
Y. Vebrianto and E. R. Widasari, “Evaluasi Kinerja Mikrokontroler Low-Power dalam Penerapan Convolutional Neural Network untuk Kendali Lengan Prostetik Bionik,” vol. 10, no. 4, pp. 1–12, 2026.
M. Athooyaa, M. P. F. Firmansyah, D. Djuniadi, and A. Ardhiansyah, “Simulasi Komparatif: Empat Algoritma Penjadwalan CPU dengan Pemodelan Interupsi I/O Menggunakan OS-SIM,” ELECTRON J. Ilm. Tek. Elektro, vol. 7, no. 1, pp. 11–21, 2026.
A. R. Fauzi, M. Zaky, R. A. Pratama, R. Khoerunnisa, and P. Pro, “Analisis Pengaruh Kapasitas RAM terhadap Kinerja Sistem Saat Menjalankan Aplikasi Berat,” vol. 18, no. 2, pp. 1–9, 2024.
