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- | ===== ISCA 2024 Tutorial on Memory-Centric Computing Systems (Half Day) ===== | + | ===== HEART 2024 Tutorial on Memory-Centric Computing Systems (Half Day) ===== |
==== Tutorial Description ==== | ==== Tutorial Description ==== | ||
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Recent PIM products and prototypes place compute units near the memory arrays. New memory interfaces like CXL (Compute Express Link) aid the enablement of compute-capable memories. At the same time, academia and industry are actively exploring other types of PIM by, e.g., exploiting the analog operation of DRAM, SRAM, flash memory, and emerging non-volatile memories, and hybrid PIM architectures that combine processing capabilities of different types and at different parts of the memory/ | Recent PIM products and prototypes place compute units near the memory arrays. New memory interfaces like CXL (Compute Express Link) aid the enablement of compute-capable memories. At the same time, academia and industry are actively exploring other types of PIM by, e.g., exploiting the analog operation of DRAM, SRAM, flash memory, and emerging non-volatile memories, and hybrid PIM architectures that combine processing capabilities of different types and at different parts of the memory/ | ||
- | {{:memory_centric_comp_banner.jpeg?400 |}} | + | {{:heart24_banner.jpeg?400 |}} |
PIM can improve performance and energy efficiency for many modern applications, | PIM can improve performance and energy efficiency for many modern applications, | ||
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However, there are many open questions spanning the entire computing stack and many challenges for widespread adoption. For example, it is critical to (1) develop programming frameworks and tools that can lower the learning curve and ease the adoption of PIM systems, (2) develop methods to identify what type of PIM would be useful for what workload, and (3) design system and security mechanisms that enable PIM in a wider scale. Implications of PIM on all aspects of computing systems and workloads is a challenging and exciting field of study. | However, there are many open questions spanning the entire computing stack and many challenges for widespread adoption. For example, it is critical to (1) develop programming frameworks and tools that can lower the learning curve and ease the adoption of PIM systems, (2) develop methods to identify what type of PIM would be useful for what workload, and (3) design system and security mechanisms that enable PIM in a wider scale. Implications of PIM on all aspects of computing systems and workloads is a challenging and exciting field of study. | ||
- | This tutorial focuses on the latest advances in PIM technology, spanning both hardware and software, including novel PIM ideas, different tools and frameworks to conduct PIM research, and programming techniques and optimization strategies for PIM kernels. We will (1) provide an introduction to PIM and the taxonomy of PIM systems, (2) give an overview and a rigorous analysis of existing PIM hardware from industry and academia, (3) provide and describe hardware and software infrastructures that can enable new and experienced researchers to conduct research in PIM systems, and (4) shed light on how to improve future PIM systems for emerging memory-bound workloads. | + | This tutorial focuses on the latest advances in PIM technology, spanning both hardware and software, including novel PIM ideas, different tools and frameworks to conduct PIM research, and programming techniques and optimization strategies for PIM kernels. We will (1) provide an introduction to PIM and the taxonomy of PIM systems, (2) give an overview and a rigorous analysis of existing PIM hardware from industry and academia, (3) provide and describe hardware and software infrastructures that can enable new and experienced researchers to conduct research in PIM systems, and (4) shed light on how to improve future PIM systems for emerging memory-bound workloads. |
==== Livestream ==== | ==== Livestream ==== | ||
- | [[https:// | + | [[https:// |
- | {{youtube> | + | {{youtube> |
==== Organizers ==== | ==== Organizers ==== | ||
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|[[https:// | |[[https:// | ||
- | ===== Agenda ===== | + | ===== Agenda |
- | ==== Lectures (tentative schedule) ==== | + | ==== Lectures (tentative schedule, time zone: UTC+1) ==== |
+ | * 10:30 am-11:00 am, Prof. Onur Mutlu / Geraldo F. Oliveira, " | ||
+ | * Introduction: | ||
+ | * PIM taxonomy: technology, location, and nature of computation (e.g., PNM (processing-near-memory) and PUM (processing-using-memory). | ||
+ | * Advances in different types of PIM at different parts of the memory/ | ||
+ | * Research challenges and opportunities in PIM systems, with a focus on enabling adoption in the real world. | ||
+ | * 11:00 am-11:20 am, Geraldo F. Oliveira, " | ||
+ | * Example real-world PNM systems: UPMEM PIM, Samsung HBM-PIM & CXL-PNM, SK Hynix AiM & CMS 2.0, Samsung AxDIMM, Alibaba PNM, Mythic. | ||
+ | * 11:30 am-12:00 pm, Geraldo F. Oliveira, "PUM Systems for Bulk Bitwise Operations." | ||
+ | * PUM systems for bulk bitwise operations in simulated and off-the-shelf memory technologies (DRAM, SRAM, and NVM). | ||
- | | + | * 12:30 pm-02:00pm, Lunch break. |
- | - Workload analysis and system bottlenecks. | + | |
- | - PIM taxonomy: technology, location, and nature of computation (e.g., PNM (processing-near-memory) and PUM (processing-using-memory). | + | |
- | - Advances in different types of PIM at different parts of the memory/ | + | |
- | - Example real-world PNM systems: UPMEM PIM, Samsung HBM-PIM & CXL-PNM, SK Hynix AiM & CMS 2.0, Samsung AxDIMM, Alibaba PNM, Mythic. | + | |
- | - PUM systems | + | |
- | | + | * Optional - Hands-on Lab: Programming |
- | | + | |
- | - Research challenges | + | |
==== Tutorial Materials ==== | ==== Tutorial Materials ==== | ||
+ | |||
^ Time ^ Speaker ^ Title ^ Materials ^ | ^ Time ^ Speaker ^ Title ^ Materials ^ | ||
- | | TBA | + | | 10: |
+ | | 11: | ||
+ | | 11: | ||
+ | | 12: | ||
+ | | 02: | ||
+ | | 02: | ||
==== Learning Materials ==== | ==== Learning Materials ==== |
start.1714119357.txt.gz · Last modified: 2024/05/22 12:44 (external edit)