How to tune slow running SQLs in PostgreSQL? See this to know (with screenshots) -
1. See the explain plan and analyze the slow running query
2. Some basic tips for tuning the query
Thin client server capacity planning for sm esLimesh Parekh
Contact us if you need any help. www.ens.net.in
Using Thin Clients and still confused about Server Capacity Planning ?
Here we have complete Server Capacity Planning guidelines for SMEs.
Massed Refresh: An Energy-Efficient Technique to Reduce Refresh Overhead in H...Ishan Thakkar
This paper presents a novel, energy-efficient DRAM re-fresh technique called massed refresh that simultaneously leverages bank-level and subarray-level concurrency to reduce the overhead of distributed refresh operations in the Hybrid Memory Cube (HMC). In massed refresh, a bundle of DRAM rows in a refresh operation is composed of two subgroups mapped to two different banks, with the rows of each subgroup mapped to different subarrays within the corresponding bank. Both subgroups of DRAM rows are refreshed concurrently during a refresh com-mand, which greatly reduces the refresh cycle time and improves bandwidth and energy efficiency of the HMC. Our experimental analysis shows that the proposed massed refresh technique achieves up to 6.3% and 5.8% improvements in throughput and energy-delay product on average over JEDEC standardized distributed per-bank refresh and state-of-the-art scattered refresh tech-niques.
How to tune slow running SQLs in PostgreSQL? See this to know (with screenshots) -
1. See the explain plan and analyze the slow running query
2. Some basic tips for tuning the query
Thin client server capacity planning for sm esLimesh Parekh
Contact us if you need any help. www.ens.net.in
Using Thin Clients and still confused about Server Capacity Planning ?
Here we have complete Server Capacity Planning guidelines for SMEs.
Massed Refresh: An Energy-Efficient Technique to Reduce Refresh Overhead in H...Ishan Thakkar
This paper presents a novel, energy-efficient DRAM re-fresh technique called massed refresh that simultaneously leverages bank-level and subarray-level concurrency to reduce the overhead of distributed refresh operations in the Hybrid Memory Cube (HMC). In massed refresh, a bundle of DRAM rows in a refresh operation is composed of two subgroups mapped to two different banks, with the rows of each subgroup mapped to different subarrays within the corresponding bank. Both subgroups of DRAM rows are refreshed concurrently during a refresh com-mand, which greatly reduces the refresh cycle time and improves bandwidth and energy efficiency of the HMC. Our experimental analysis shows that the proposed massed refresh technique achieves up to 6.3% and 5.8% improvements in throughput and energy-delay product on average over JEDEC standardized distributed per-bank refresh and state-of-the-art scattered refresh tech-niques.
With stunning harbour, iconic beaches, surely Sydney can offers travelers plenty of fun things to do, this is our top 10 ultimate Sydney experience, what do you think?
With stunning harbour, iconic beaches, surely Sydney can offers travelers plenty of fun things to do, this is our top 10 ultimate Sydney experience, what do you think?
Internet of Things (IoT) data frequently has a location and time component. Getting value out of this "geotemporal" data can be tricky. We'll explore when and how to leverage Cassandra, DSE Search and DSE Analytics to surface meaningful information from your geotemporal data.
Controlling Memory Footprint at All Layers: Linux Kernel, Applications, Libra...peknap
Reducing memory usage is well covered in the history of this conference, yet new tricks still do exist. When optimizing memory footprint for an home gateway device, the author found some unexpected places where small changes can save valuable amount of DRAM or Flash space. This talk will visit different areas including - Kernel: fragmentation threshold, page frame reclamation task and atomic memory. Application level: Memory inefficient shared libraries due to ABI compliance and dynamic loading. Toolchain: Tuning malloc allocator parameters and compiler options. System level: General kernel might be more memory efficient than MMU-less uClinux, and preventing lock up when the system is on the brink of running out of memory.
The current technological revolution around the world has made the world faster with the
advancements in sophisticated computer devices. Computer, as a digital machine, enables people
to work faster than ever before. The memory of this device is a great feature of this digital tool.
RAM, Random Access Memory is the primary tool of data storage that is inserted in the
integrated circuit while data can be accessed in any sequence or randomly. Thus it is termed
RAM or Random Access Memory.
The journey of dynamic and static RAM was initiated in 1960s which can readily
developed in 1970s. Now a days the technology is much more user friendly. RAM is further
divided into three types:
• Dynamic RAM (DRAM)
• Static RAM (SRAM)
• Non-volatile RAM (NVRAM = RAM + Battery)
but we will discuss only first two i.e. (DRAM and SRAM).
Dynamic RAM is the most common memory used now a days. Inside of the RAM chip
there is a memory cell that holds one bit of information and is divided into further two parts: a
transistor and a capacitor. The capacitor holds the bit of information as a state of 0 or 1 and the
transistor acts as a switch that lets the control circuitry on the memory chip that reads the
capacitor or change its state. The capacitor is like a small bucket that stores the electrons in it. To
store 1, bucket gets filled with electrons and to store 0 buckets gets empty. The problem with the
capacitor’s bucket is that it has a leak and in a matter of few seconds a full buckets becomes
empty. Therefore they need to be recharged continuously in order to work properly and because
of this reason it has been given the name Dynamic RAM. This refreshing phenomenon is time
consuming as well.
In static RAM a flip-flop holds each bit of a memory. A flip-flop memory cell takes 4 to
6 transistors along with the wiring. Due to this reason they draws current all the time and gets
warm easily, therefore, they cannot be packed together tightly. They do not require any
refreshing method though, therefore, they are very fast memory chips.
Caches are used in many layers of applications that we develop today, holding data inside or outside of your runtime environment, or even distributed across multiple platforms in data fabrics. However, considerable performance gains can often be realized by configuring the deployment platform/environment and coding your application to take advantage of the properties of CPU caches.
In this talk, we will explore what CPU caches are, how they work and how to measure your JVM-based application data usage to utilize them for maximum efficiency. We will discuss the future of CPU caches in a many-core world, as well as advancements that will soon arrive such as HP's Memristor.
Similar to High Endurance Last Level Hybrid Cache Design (20)
1. High Endurance Hybrid Cache
Design with Access Aware
policies and Dynamic Cache
Partitioning
By Thallam Keerthi
Under Guidance of Mrs.Namitha Palecha
RVCE VLSI Design and Embedded systems
3. Problem DescriptionProblem Description
Increasing frequency of operations on one core-
increases the heat Dissipation
CMP – Chip Multiprocessors solves the issue without
increasing the frequency of each core
Last level cache(LLC) – Shared memory for cores –
Usually composed of SRAM’s – High leakage power
4. Problem DescriptionProblem Description
SRAM STT-RAM
Density 1X 4X
Read Time Very fast Fast
Write Time Very fast Slow
Read Energy Low Low
Write Energy Low High
Leakage Energy High Low
Endurance 10^16 4*10^12
SRAM has high leakage power and STT-RAM requires
high write energy and write latency is more
5. Hybrid Cache ArchitectureHybrid Cache Architecture
Problem: Local Bank
suffers from more
write counts and
wears out fast.
Non-Uniform
distribution of
workload among
different memory
banks
6. Hybrid Cache ArchitectureHybrid Cache Architecture
Part of local bank consists of
SRAM cells and remaining
part consists of STT-RAM cells
This decreases the write
pressure on the local bank
(Banks)
(Write
count)
Showing the unequal workload
7. Hybrid Cache ArchitectureHybrid Cache Architecture
All writes on non-hybrid local bank are
redirected to SRAM bank and only few writes of
local hybrid bank are redirected to SRAM cell
10. Access Aware PoliciesAccess Aware Policies
Dynamic Cache Partitioning
1) Which Partition size needs to be changed
2) Which region in a partition needs to be changed
• Ideally WPSW should be high
•WPNW should be minimum or
less
16. ConclusionConclusion
CMP Architecture – No. of operations can be
increased working with same frequency
Hybrid Cache – Balances the write distribution
among the banks
Access Aware Policies – increases the write
utilization of SRAM and decreases the
endurance problem of STT-RAM cells
Dynamic Cache Partitioning – Decreases the
hit latency, decreases the cache miss rate.