Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Amazon EC2 Choices?

    I'm curious as to how many folks out there have used the Amazon EC2 compute services to run 2nd gen sequencing analyses "in the cloud" and particularly which particular compute offerings you chose.

    For those who haven't looked at this, Amazon has a variety of compute schemes which can be rented by the hour which differ in the amount of RAM, local storage & compute power. I'm trying to get a handle on how to map these onto real world compute problems -- working with vertebrate genomes using BWA, Bowtie, BFAST, TopHat, dindel, etc.

    A quick table I've assembled from Amazon's own specs;
    Code:
    Family	        Name	                        Gb RAM	EC2	Gb Disk	Bits	I/O
    Standard	Large		7.500	4.0	850	64	high
    Standard	Extra Large	15.000	8.0	1,690	64	high
    High-Memory	Extra Large	17.100	6.5	   420	64	moderate
    High-Memory	Double Extra Large	34.200	13.0	  850	64	high
    High-Memory	Quadruple Extra Large	68.400	26.0	1,690	64	high
    High-CPU	Extra Large		7.000	20.0	1,690	64	high
    Cluster Compute	Quadruple Extra Large	23.000	33.5	1,690	64	very high
    I've left out the "Micro" instance as I'm still trying to figure out what it does, and have also left out the 32-bit options.

    EC2 here is their attempt to estimate performance; apparently 1 EC2 is equivalent to a 1.7Ghz Xenon processor with generally 2 cores per processor.

    Pricing is on a different matrix I'm still digesting (there are 3 pricing models for the above classes of machines), but basically within a family each supersizing costs you double -- extra large is twice large and quadruple is another doubling of that.

    So, which is a good choice? And in running multithreaded applications, would I go with 1 thread per core or 1 per EC2?

Latest Articles

Collapse

  • seqadmin
    Best Practices for Single-Cell Sequencing Analysis
    by seqadmin



    While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
    06-06-2024, 07:15 AM
  • seqadmin
    Latest Developments in Precision Medicine
    by seqadmin



    Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

    Somatic Genomics
    “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
    05-24-2024, 01:16 PM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, Today, 07:23 AM
0 responses
8 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-17-2024, 06:54 AM
0 responses
11 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-14-2024, 07:24 AM
0 responses
24 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-13-2024, 08:58 AM
0 responses
17 views
0 likes
Last Post seqadmin  
Working...
X