정이품 교수

The ever-growing demands for memory with larger capacity and higher bandwidth have driven recent innovations on memory expansion and disaggregation technologies based on Compute eXpress Link (CXL). Especially, CXL-based memory expansion technology has recently gained notable attention for its ability not only to economically expand memory capacity and bandwidth but also to decouple memory technologies from a specific memory interface of the CPU. However, since CXL memory devices have not been wi

As semiconductor power density is no longer constant with the technology process scaling down, we need different solutions if we are to continue scaling application performance. To this end, modern CPUs are integrating capable data accelerators on the chip, aiming to improve performance and efficiency for a wide range of applications and usages. One such accelerator is the Intel® Data Streaming Accelerator (DSA) introduced since Intel® 4th Generation Xeon® Scalable CPUs (Sapphire Rapids). DSA ta

A growing demand for hyperscale services has compelled hyperscalers to deploy more compute resources at an unprecedented pace, further accelerated by the demise of Dennard scaling. Meanwhile, a considerable portion of the compute resources are consumed to execute common functions present across the hyperscale services, i.e., datacenter taxes. These challenges motivated many to explore specialized accelerators for these functions. Leading such a technology trend, Intel has integrated diverse on-c

The performance gap between in-order (InO) and out-of-order (OoO) cores comes from the ability to dynamically create highly optimized instruction issue schedules. In this work, we observe that a significant amount of performance benefit of OoO scheduling can also be attained by supplementing a traditional InO core with a small and speculative instruction scheduling window, namely SpecInO. SpecInO monitors a small set of instructions ahead of a conventional InO scheduling window, aiming at issuin

CXL is the latest interconnect technology built on PCIe, providing three protocols to facilitate three distinct types of devices, each with unique capabilities. Among these devices, a CXL Type-2 device has become commercially available, followed by CXL Type-3 devices. Therefore, it is timely to understand capabilities and characteristics of the CXL Type-2 device, as well as explore suitable applications. In this work, first, we delve into three key features of a CXL Type-2 device: cache-coherent

Row Hammer (RH) has been demonstrated as a security vulnerability in modern systems. Although commodity CPUs can handle RH-induced single-bit errors in DRAM through ECC, RH can still give rise to multi-bit uncorrectable errors (UEs) and crash the systems. Meanwhile, recent work has indicated that the DRAM cells vulnerable to RH are determined by manufacturing imperfections and resulting defects. Taking one step further from the recent work, we first conduct RH experiments on contemporary DRAM mo

This paper presents a scalable page cache called ScaleCache for improving SSD scalability. Specifically, we first propose a concurrent data structure of page cache based on XArray (ccXArray) to enable access and update the page cache concurrently. Second, we introduce a direct page flush (dflush) which directly flushes pages to storage devices in a parallel and opportunistic manner. We implement ScaleCache with two techniques in the Linux kernel and evaluate it on a 64-core machine with eight NV

Out-of-order cores provide high performance at the cost of energy efficiency. Dynamic scheduling is one of the major contributors to this: generating highly optimized issue schedules considering both data dependences and underlying execution resources, but relying heavily on complex wakeup and select operations of an out-of-order issue queue (IQ). For decades, researchers have proposed several complexity-effective dynamic scheduling schemes by leveraging the energy efficiency of an in-order IQ.

A typical SmartNIC (SNIC) integrates a processor comprising Arm CPU and accelerators with a conventional NIC. The processor is designed to energy-efficiently execute network functions frequently used by datacenter applications. With such a processor, the SNIC has promised to notably improve the system-wide energy efficiency of datacenter servers. Nevertheless, the latest trend of integrating accelerators into server CPUs for these functions sparks a question on the SNIC processor’s superiority o

Spin-transfer torque magnetic random-access memory (STT-MRAM) is an emerging nonvolatile memory technology that has been received significant attention due to its higher density and lower leakage current over SRAM. One compelling use case is to employ STT-MRAM as a graphics processing unit (GPU) register file (RF) to reduce its massive energy consumption. One critical challenge is that STT-MRAM has longer access latency and higher dynamic power consumption than SRAM, which motivates the hierarch

In large-scale analytics, in-storage processing (ISP) can significantly boost query performance by letting ISP engines (e.g., FPGAs) preselect only the relevant data before sending them to databases.This reduces the amount of not only data transfer between storage and host, but also database computation, facilitating faster query processing.However, existing ISP solutions cannot effectively support a wide range of modern analytical queries because they only support simple combinations of frequen

Graphics processing units (GPUs) achieve high throughput by exploiting a high degree of thread-level parallelism (TLP). To support such high TLP, GPUs have a large-sized register file to store the context of all threads, consuming around 20% of total GPU energy. Several previous studies have attempted to minimize the energy consumption of the register file by implementing an emerging non-volatile memory (NVM), leveraging its higher density and lower leakage power over SRAMs. To amortize the cost

The advancement in I/O technology has posed an unprecedented demand for high-performance processing on I/O data, leading to the development of Data Direct I/O (DDIO) technology. DDIO improves I/O processing efficiency by directly injecting all inbound I/O data into the last-level cache (LLC) in cooperation with any type of I/O device. Nonetheless, in certain scenarios with more than one I/O applications, DDIO may have sub-optimal performance caused by interference inside the LLC, resulting in th

Tensor cores in the recent NVIDIA GPUs are under the spotlight due to their superior computation throughput for general matrix-matrix multiplication (GEMM) that has been widely used for deep learning applications. For massive-scale GEMMs, the entire matrix is practically divided into sub-matrices and assigned to multiple thread blocks and warps, and then processed by the tensor cores. Meanwhile, the same sub-matrix is regularly reused as an input to different sub-GEMMs, which causes redundant lo